From f4522ad0e968bc1f4a3fc2b8761c920bdaa992b0 Mon Sep 17 00:00:00 2001 From: Justin Wilkins Date: Tue, 25 Aug 2020 10:11:50 +0200 Subject: [PATCH] Add docs --- .gitignore | 1 - docs/404.html | 160 ++++ docs/articles/index.html | 159 ++++ docs/articles/pk-curves.html | 750 ++++++++++++++++++ .../figure-html/1cptdemo-1.png | Bin 0 -> 52713 bytes .../figure-html/1cptssdemo-1.png | Bin 0 -> 53887 bytes .../figure-html/2cptdemo-1.png | Bin 0 -> 51999 bytes .../figure-html/2cptssdemo-1.png | Bin 0 -> 54172 bytes .../figure-html/3cptdemo-1.png | Bin 0 -> 53435 bytes .../figure-html/3cptssdemo-1.png | Bin 0 -> 54806 bytes .../figure-html/pkcurve1-1.png | Bin 0 -> 15957 bytes docs/authors.html | 187 +++++ docs/bootstrap-toc.css | 60 ++ docs/bootstrap-toc.js | 159 ++++ docs/docsearch.css | 148 ++++ docs/docsearch.js | 85 ++ docs/index.html | 149 ++++ docs/link.svg | 12 + docs/news/index.html | 181 +++++ docs/pkgdown.css | 367 +++++++++ docs/pkgdown.js | 108 +++ docs/pkgdown.yml | 7 + 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docs/reference/calc_ss_2cmt.html create mode 100644 docs/reference/calc_ss_3cmt.html create mode 100644 docs/reference/gcv_convert.html create mode 100644 docs/reference/get_auc.html create mode 100644 docs/reference/get_est_table.html create mode 100644 docs/reference/get_omega.html create mode 100644 docs/reference/get_probinfo.html create mode 100644 docs/reference/get_shrinkage.html create mode 100644 docs/reference/get_sigma.html create mode 100644 docs/reference/get_theta.html create mode 100644 docs/reference/gm.html create mode 100644 docs/reference/index.html create mode 100644 docs/reference/pcv.html create mode 100644 docs/reference/pk_curve-1.png create mode 100644 docs/reference/pk_curve.html create mode 100644 docs/reference/plot_nmprogress.html create mode 100644 docs/reference/plot_scm.html create mode 100644 docs/reference/read_nm.html create mode 100644 docs/reference/read_nm_all.html create mode 100644 docs/reference/read_nm_multi_table.html create mode 100644 docs/reference/read_nm_std_ext.html create mode 100644 docs/reference/read_nmcov.html create mode 100644 docs/reference/read_nmext.html create mode 100644 docs/reference/read_nmtables.html create mode 100644 docs/reference/read_scm.html create mode 100644 docs/reference/rnm.html create mode 100644 docs/reference/sample_omega.html create mode 100644 docs/reference/sample_sigma.html create mode 100644 docs/reference/sample_uncert.html create mode 100644 docs/reference/table_rtf.html diff --git a/.gitignore b/.gitignore index 0d7f03b..c833a2c 100644 --- a/.gitignore +++ b/.gitignore @@ -2,5 +2,4 @@ .Rhistory .RData .Ruserdata -docs inst/doc diff --git a/docs/404.html b/docs/404.html new file mode 100644 index 0000000..3d50b30 --- /dev/null +++ b/docs/404.html @@ -0,0 +1,160 @@ + + + + + + + + +Page not found (404) • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
+
+
+

Page not found (404)

+
+ +Content not found. Please use links in the navbar. + +
+ + + +
+ + + +
+
+

Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

+
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+

Site built with pkgdown 1.5.1.

+
+ +
+
+ + + + + + + + diff --git a/docs/articles/index.html b/docs/articles/index.html new file mode 100644 index 0000000..d160e97 --- /dev/null +++ b/docs/articles/index.html @@ -0,0 +1,159 @@ + + + + + + + + +Articles • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Articles

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All vignettes

+

+ +
+
Drawing PK curves with pmxTools
+
+
+
+
+
+ + +
+
+

Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

+
+ +
+

Site built with pkgdown 1.5.1.

+
+ +
+
+ + + + + + + + diff --git a/docs/articles/pk-curves.html b/docs/articles/pk-curves.html new file mode 100644 index 0000000..853294b --- /dev/null +++ b/docs/articles/pk-curves.html @@ -0,0 +1,750 @@ + + + + + + + +Drawing PK curves with pmxTools • pmxTools + + + + + + + + + + +
+
+ + + + +
+
+
+

Drawing PK curves with pmxTools

+ + + Source: vignettes/pk-curves.Rmd + + +
+ + + +
library(pmxTools)
+library(gridExtra)
+

pmxTools includes functions for constructing pharmacokinetic (PK) concentration-time curves for a range of common compartmental systems using PK parameters and microconstants. The underlying solutions are based on Julie Bertrand and France Mentré’s Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models implemented in the Monolix software, published in 2008.

+

The options available are by necessity confined to one-, two- and three-compartmental linear models with intravenous bolus, infusion or oral dosing (the latter with zero- or first-order absorption). If more complex systems are needed, you are probably better off using an ODE-based simulation package such as RxODE or mrgSolve.

+
+

+Specifying model parameters

+

Models take dose, time and PK parameters as inputs. Names for some PK parameters, especially volumes and intercompartmental clearances, vary by model type.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ParameterDescriptionUsed for
tTimeSingle-dose
tadTime after last doseSteady state
doseDoseAll
CLClearanceAll
+V, V1 +Central volume of distributionAll
V2First peripheral volume of distributionTwo- and three-compartment models
V3Second peripheral volume of distributionThree-compartment models
+Q, Q1, Q2 +Intercompartmental clearance (between V1 and V2)Two- and three-compartment models
Q3Intercompartmental clearance (between V1 and V3)Three-compartment models
tlagLag timeModels with lag time
tinfDuration of infusionModels with infusion
durDuration of zero-order absorptionModels with zero-order absorption
kaFirst-order absorption rateModels with first-order absorption
+
+
+

+One-compartment, single dose

+

Available functions include:

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ModelVariantCall
1-compartmentSingle-dose, boluscalc_sd_1cmt_linear_bolus(t, dose, CL, V)
 Single-dose, infusioncalc_sd_1cmt_linear_infusion(t, dose, CL, V, tinf)
 Single-dose, zero-order oral absorptioncalc_sd_1cmt_linear_oral_0(t, dose, CL, V, dur)
 Single-dose, zero-order oral absorption with lag timecalc_sd_1cmt_linear_oral_0_lag(t, dose, CL, V, dur, tlag)
 Single-dose, first-order oral absorptioncalc_sd_1cmt_linear_oral_1(t, dose, CL, V, ka)
 Single-dose, first-order oral absorption with lag timecalc_sd_1cmt_linear_oral_1_lag(t, dose, CL, V, ka, tlag)
+

For example -

+
+library(ggplot2)
+
+t <- seq(0, 24, by=0.1)
+
+df1 <- data.frame(t = t,
+                  Cp1 = calc_sd_1cmt_linear_bolus(t = t, dose = 600, CL = 5, V = 20),
+                  Cp2 = calc_sd_1cmt_linear_infusion(t = t, dose = 600, CL = 5, V = 20, tinf=2),
+                  Cp3 = calc_sd_1cmt_linear_oral_0(t = t, dose = 600, CL = 5, V = 20, dur=2),
+                  Cp4 = calc_sd_1cmt_linear_oral_0_lag(t = t, dose = 600, CL = 5, V = 20, dur=2, tlag=1),
+                  Cp5 = calc_sd_1cmt_linear_oral_1(t = t, dose = 600, CL = 5, V = 20, ka=1.5),
+                  Cp6 = calc_sd_1cmt_linear_oral_1_lag(t = t, dose = 600, CL = 5, V = 20, ka=1.5, tlag=1))
+
+p1.1 <- ggplot(df1, aes(t, Cp1)) +
+  geom_line() +
+  labs(title="Bolus dose")
+
+p1.2 <- ggplot(df1, aes(t, Cp2)) +
+  geom_line() +
+  labs(title="Infusion")
+
+p1.3 <- ggplot(df1, aes(t, Cp3)) +
+  geom_line() +
+  labs(title="Zero-order oral")
+
+p1.4 <- ggplot(df1, aes(t, Cp4)) +
+  geom_line() +
+  labs(title="Zero-order oral with lag time")
+
+p1.5 <- ggplot(df1, aes(t, Cp5)) +
+  geom_line() +
+  labs(title="First-order oral")
+
+p1.6 <- ggplot(df1, aes(t, Cp6)) +
+  geom_line() +
+  labs(title="First-order oral with lag time")
+
+grid.arrange(p1.1, p1.2, p1.3, p1.4, p1.5, p1.6, nrow=3)
+

+
+
+

+One-compartment, steady state

+

Available functions include:

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ModelVariantCall
1-compartmentSteady state, boluscalc_ss_1cmt_linear_bolus(tad, tau, dose, CL, V)
 Steady state, infusioncalc_ss_1cmt_linear_infusion(tad, tau, dose, CL, V, tinf)
 Steady state, zero-order oral absorptioncalc_ss_1cmt_linear_oral_0(tad, tau, dose, CL, V, dur)
 Steady state, zero-order oral absorption with lag timecalc_ss_1cmt_linear_oral_0_lag(tad, tau, dose, CL, V, dur, tlag)
 Steady state, first-order oral absorptioncalc_ss_1cmt_linear_oral_1(tad, tau, dose, CL, V, ka)
 Steady state, first-order oral absorption with lag timecalc_ss_1cmt_linear_oral_1_lag(tad, tau, dose, CL, V, ka, tlag)
+

For example -

+
+t <- seq(0, 24, by=0.1)
+
+df1ss <- data.frame(t = t,
+                  Cp1 = calc_ss_1cmt_linear_bolus(t = t, tau = 24, dose = 600, CL = 1, V = 20),
+                  Cp2 = calc_ss_1cmt_linear_infusion(t = t, tau = 24, dose = 600, CL = 1, V = 20, tinf=2),
+                  Cp3 = calc_ss_1cmt_linear_oral_0(t = t, tau = 24, dose = 600, CL = 1, V = 20, dur=2),
+                  Cp4 = calc_ss_1cmt_linear_oral_0_lag(t = t, tau = 24, dose = 600, CL = 1, V = 20, dur=2, tlag=1.5),
+                  Cp5 = calc_ss_1cmt_linear_oral_1(t = t, tau = 24, dose = 600, CL = 1, V = 20, ka=1.5),
+                  Cp6 = calc_ss_1cmt_linear_oral_1_lag(t = t, tau = 24, dose = 600, CL = 1, V = 20, ka=1.5, tlag=1.5))
+
+p1.1ss <- ggplot(df1ss, aes(t, Cp1)) +
+  geom_line() +
+  labs(title="Bolus dose")
+
+p1.2ss <- ggplot(df1ss, aes(t, Cp2)) +
+  geom_line() +
+  labs(title="Infusion")
+
+p1.3ss <- ggplot(df1ss, aes(t, Cp3)) +
+  geom_line() +
+  labs(title="Zero-order oral")
+
+p1.4ss <- ggplot(df1ss, aes(t, Cp4)) +
+  geom_line() +
+  labs(title="Zero-order oral with lag time")
+
+p1.5ss <- ggplot(df1ss, aes(t, Cp5)) +
+  geom_line() +
+  labs(title="First-order oral")
+
+p1.6ss <- ggplot(df1ss, aes(t, Cp6)) +
+  geom_line() +
+  labs(title="First-order oral with lag time")
+
+grid.arrange(p1.1ss, p1.2ss, p1.3ss, p1.4ss, p1.5ss, p1.6ss, nrow=3)
+

+
+
+

+Two-compartment, single dose

+

Available functions include:

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ModelVariantCall
2-compartmentSingle-dose, boluscalc_sd_2cmt_linear_bolus(t, dose, CL, V1, V2, Q)
 Single-dose, infusioncalc_sd_2cmt_linear_infusion(t, dose, CL, V1, V2, Q, tinf)
 Single-dose, zero-order oral absorptioncalc_sd_2cmt_linear_oral_0(t, dose, CL, V1, V2, Q, dur)
 Single-dose, zero-order oral absorption with lag timecalc_sd_2cmt_linear_oral_0_lag(t, dose, CL, V1, V2, Q, dur, tlag)
 Single-dose, first-order oral absorptioncalc_sd_2cmt_linear_oral_1(t, dose, CL, V1, V2, Q, ka)
 Single-dose, first-order oral absorption with lag timecalc_sd_2cmt_linear_oral_1_lag(t, dose, CL, V1, V2, Q, ka, tlag)
+

For example -

+
+t <- seq(0, 24, by=0.1)
+
+df2 <- data.frame(t = t,
+                  Cp1 = calc_sd_2cmt_linear_bolus(t = t, dose = 600, CL = 5, V1 = 20, V2 = 80, Q = 1),
+                  Cp2 = calc_sd_2cmt_linear_infusion(t = t, dose = 600, CL = 5, V1 = 20, V2 = 80, Q = 1, tinf=2),
+                  Cp3 = calc_sd_2cmt_linear_oral_0(t = t, dose = 600, CL = 5, V1 = 20, V2 = 80, Q = 1, dur=2),
+                  Cp4 = calc_sd_2cmt_linear_oral_0_lag(t = t, dose = 600, CL = 5, V1 = 20, V2 = 80, Q = 1, dur=2, tlag=1),
+                  Cp5 = calc_sd_2cmt_linear_oral_1(t = t, dose = 600, CL = 5, V1 = 20, V2 = 80, Q = 1, ka=1.5),
+                  Cp6 = calc_sd_2cmt_linear_oral_1_lag(t = t, dose = 600, CL = 5, V1 = 20, V2 = 80, Q = 1, ka=1.5, tlag=1))
+
+p2.1 <- ggplot(df2, aes(t, Cp1)) +
+  geom_line() +
+  labs(title="Bolus dose")
+
+p2.2 <- ggplot(df2, aes(t, Cp2)) +
+  geom_line() +
+  labs(title="Infusion")
+
+p2.3 <- ggplot(df2, aes(t, Cp3)) +
+  geom_line() +
+  labs(title="Zero-order oral")
+
+p2.4 <- ggplot(df2, aes(t, Cp4)) +
+  geom_line() +
+  labs(title="Zero-order oral with lag time")
+
+p2.5 <- ggplot(df2, aes(t, Cp5)) +
+  geom_line() +
+  labs(title="First-order oral")
+
+p2.6 <- ggplot(df2, aes(t, Cp6)) +
+  geom_line() +
+  labs(title="First-order oral with lag time")
+
+grid.arrange(p2.1, p2.2, p2.3, p2.4, p2.5, p2.6, nrow=3)
+

+
+
+

+Two-compartment, steady state

+

Available functions include:

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ModelVariantCall
2-compartmentSteady state, boluscalc_ss_2cmt_linear_bolus(tad, tau, dose, CL, V1, V2, Q)
 Steady state, infusioncalc_ss_2cmt_linear_infusion(tad, tau, dose, CL, V1, V2, Q, tinf)
 Steady state, zero-order oral absorptioncalc_ss_2cmt_linear_oral_0(tad, tau, dose, CL, V1, V2, Q, dur)
 Steady state, zero-order oral absorption with lag timecalc_ss_2cmt_linear_oral_0_lag(tad, tau, dose, CL, V1, V2, Q, dur, tlag)
 Steady state, first-order oral absorptioncalc_ss_2cmt_linear_oral_1(tad, tau, dose, CL, V1, V2, Q, ka)
 Steady state, first-order oral absorption with lag timecalc_ss_2cmt_linear_oral_1_lag(tad, tau, dose, CL, V1, V2, Q, ka, tlag)
+

For example -

+
+t <- seq(0, 24, by=0.1)
+
+df2ss <- data.frame(t = t,
+                  Cp1 = calc_ss_2cmt_linear_bolus(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 80, Q = 0.25),
+                  Cp2 = calc_ss_2cmt_linear_infusion(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 80, Q = 0.25, tinf=2),
+                  Cp3 = calc_ss_2cmt_linear_oral_0(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 80, Q = 0.25, dur=2),
+                  Cp4 = calc_ss_2cmt_linear_oral_0_lag(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 80, Q = 0.25, dur=2, tlag=1.5),
+                  Cp5 = calc_ss_2cmt_linear_oral_1(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 80, Q = 0.25, ka=1.5),
+                  Cp6 = calc_ss_2cmt_linear_oral_1_lag(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 80, Q = 0.25, ka=1.5, tlag=1.5))
+
+p2.1ss <- ggplot(df2ss, aes(t, Cp1)) +
+  geom_line() +
+  labs(title="Bolus dose")
+
+p2.2ss <- ggplot(df2ss, aes(t, Cp2)) +
+  geom_line() +
+  labs(title="Infusion")
+
+p2.3ss <- ggplot(df2ss, aes(t, Cp3)) +
+  geom_line() +
+  labs(title="Zero-order oral")
+
+p2.4ss <- ggplot(df2ss, aes(t, Cp4)) +
+  geom_line() +
+  labs(title="Zero-order oral with lag time")
+
+p2.5ss <- ggplot(df2ss, aes(t, Cp5)) +
+  geom_line() +
+  labs(title="First-order oral")
+
+p2.6ss <- ggplot(df2ss, aes(t, Cp6)) +
+  geom_line() +
+  labs(title="First-order oral with lag time")
+
+grid.arrange(p2.1ss, p2.2ss, p2.3ss, p2.4ss, p2.5ss, p2.6ss, nrow=3)
+

+
+
+

+Three-compartment, single dose

+

Available functions include:

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ModelVariantCall
3-compartmentSingle-dose, boluscalc_sd_3cmt_linear_bolus(t, dose, CL, V1, V2, V3, Q2, Q3)
 Single-dose, infusioncalc_sd_3cmt_linear_infusion(t, dose, CL, V1, V2, V3, Q2, Q3, tinf)
 Single-dose, zero-order oral absorptioncalc_sd_3cmt_linear_oral_0(t, dose, CL, V1, V2, V3, Q2, Q3, dur)
 Single-dose, zero-order oral absorption with lag timecalc_sd_3cmt_linear_oral_0_lag(t, dose, CL, V1, V2, V3, Q2, Q3, dur, tlag)
 Single-dose, first-order oral absorptioncalc_sd_3cmt_linear_oral_1(t, dose, CL, V1, V2, V3, Q2, Q3, ka)
 Single-dose, first-order oral absorption with lag timecalc_sd_3cmt_linear_oral_1_lag(t, dose, CL, V1, V2, V3, Q2, Q3, ka, tlag)
+

For example -

+
+t <- seq(0, 24, by=0.1)
+
+df3 <- data.frame(t = t,
+                  Cp1 = calc_sd_3cmt_linear_bolus(t = t, CL = 3.5, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 600),
+                  Cp2 = calc_sd_3cmt_linear_infusion(t = t, CL = 3.5, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 600, tinf=2),
+                  Cp3 = calc_sd_3cmt_linear_oral_0(t = t, CL = 3.5, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 600, dur=2),
+                  Cp4 = calc_sd_3cmt_linear_oral_0_lag(t = t, CL = 3.5, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 600, dur=2, tlag=1),
+                  Cp5 = calc_sd_3cmt_linear_oral_1(t = t, CL = 3.5, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 600, ka=1.5),
+                  Cp6 = calc_sd_3cmt_linear_oral_1_lag(t = t, CL = 3.5, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 600, ka=1.5, tlag=1))
+
+p3.1 <- ggplot(df3, aes(t, Cp1)) +
+  geom_line() +
+  labs(title="Bolus dose")
+
+p3.2 <- ggplot(df3, aes(t, Cp2)) +
+  geom_line() +
+  labs(title="Infusion")
+
+p3.3 <- ggplot(df3, aes(t, Cp3)) +
+  geom_line() +
+  labs(title="Zero-order oral")
+
+p3.4 <- ggplot(df3, aes(t, Cp4)) +
+  geom_line() +
+  labs(title="Zero-order oral with lag time")
+
+p3.5 <- ggplot(df3, aes(t, Cp5)) +
+  geom_line() +
+  labs(title="First-order oral")
+
+p3.6 <- ggplot(df3, aes(t, Cp6)) +
+  geom_line() +
+  labs(title="First-order oral with lag time")
+
+grid.arrange(p3.1, p3.2, p3.3, p3.4, p3.5, p3.6, nrow=3)
+

+
+
+

+Three-compartment, steady state

+

Available functions include:

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ModelVariantCall
3-compartmentSingle-dose, boluscalc_ss_3cmt_linear_bolus(tad, tau, dose, CL, V1, V2, V3, Q2, Q3)
 Single-dose, infusioncalc_ss_3cmt_linear_infusion(tad, tau, dose, CL, V1, V2, V3, Q2, Q3, tinf)
 Single-dose, zero-order oral absorptioncalc_ss_3cmt_linear_oral_0(tad, tau, dose, CL, V1, V2, V3, Q2, Q3, dur)
 Single-dose, zero-order oral absorption with lag timecalc_ss_3cmt_linear_oral_0_lag(tad, tau, dose, CL, V1, V2, V3, Q2, Q3, dur, tlag)
 Single-dose, first-order oral absorptioncalc_ss_3cmt_linear_oral_1(tad, tau, dose, CL, V1, V2, V3, Q2, Q3, ka)
 Single-dose, first-order oral absorption with lag timecalc_ss_3cmt_linear_oral_1_lag(tad, tau, dose, CL, V1, V2, V3, Q2, Q3, ka, tlag)
+

For example -

+
+t <- seq(0, 24, by=0.1)
+
+df3ss <- data.frame(t = t,
+                  Cp1 = calc_ss_3cmt_linear_bolus(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05),
+                  Cp2 = calc_ss_3cmt_linear_infusion(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, tinf=2),
+                  Cp3 = calc_ss_3cmt_linear_oral_0(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dur=2),
+                  Cp4 = calc_ss_3cmt_linear_oral_0_lag(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, dur=2, tlag=1.5),
+                  Cp5 = calc_ss_3cmt_linear_oral_1(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, ka=1.5),
+                  Cp6 = calc_ss_3cmt_linear_oral_1_lag(tad = t, tau = 24, dose = 600, CL = 1, V1 = 20, V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, ka=1.5, tlag=1.5))
+
+p3.1ss <- ggplot(df3ss, aes(t, Cp1)) +
+  geom_line() +
+  labs(title="Bolus dose")
+
+p3.2ss <- ggplot(df3ss, aes(t, Cp2)) +
+  geom_line() +
+  labs(title="Infusion")
+
+p3.3ss <- ggplot(df3ss, aes(t, Cp3)) +
+  geom_line() +
+  labs(title="Zero-order oral")
+
+p3.4ss <- ggplot(df3ss, aes(t, Cp4)) +
+  geom_line() +
+  labs(title="Zero-order oral with lag time")
+
+p3.5ss <- ggplot(df3ss, aes(t, Cp5)) +
+  geom_line() +
+  labs(title="First-order oral")
+
+p3.6ss <- ggplot(df3ss, aes(t, Cp6)) +
+  geom_line() +
+  labs(title="First-order oral with lag time")
+
+grid.arrange(p3.1ss, p3.2ss, p3.3ss, p3.4ss, p3.5ss, p3.6ss, nrow=3)
+

+
+
+

+Multiple dosing

+

Being able to display single-dose and steady state curves for various commonly-seen systems is all very well but it is often more useful to show a concentration-time curve which demonstrates accumulation and time to steady state. The pk_curve() function makes this straightforward by using the principle of superposition.

+
+dfcurve1 <- pk_curve(t=seq(0,168,by=0.1), model="3cmt_oral", ii=24, addl=12,
+                     params=list(CL=1.5, V1=25, V2=2, V3=5, Q2=0.5, Q3=0.25, ka=1))
+
+ggplot(dfcurve1, aes(t, cp)) +
+  geom_line()
+

+
+
+ + + +
+ + + +
+

Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

+
+ +
+

Site built with pkgdown 1.5.1.

+
+ +
+
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Authors

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    Justin Wilkins. Author, maintainer. +

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    Bill Denney. Author. +

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    Rik Schoemaker. Author. +

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    Leonid Gibiansky. Contributor. +

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    Andrew Hooker. Contributor. +

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    E. Niclas Jonsson. Contributor. +

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    Mats O. Karlsson. Contributor. +

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    John Johnson. Contributor. +

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Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

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Site built with pkgdown 1.5.1.

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+
+ + + + + + + + diff --git a/docs/bootstrap-toc.css b/docs/bootstrap-toc.css new file mode 100644 index 0000000..5a85941 --- /dev/null +++ b/docs/bootstrap-toc.css @@ -0,0 +1,60 @@ +/*! + * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/) + * Copyright 2015 Aidan Feldman + * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */ + +/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */ + +/* All levels of nav */ +nav[data-toggle='toc'] .nav > li > a { + display: block; + padding: 4px 20px; + font-size: 13px; + font-weight: 500; + color: #767676; +} +nav[data-toggle='toc'] .nav > li > a:hover, +nav[data-toggle='toc'] .nav > li > a:focus { + padding-left: 19px; + color: #563d7c; + text-decoration: none; + background-color: transparent; + border-left: 1px solid #563d7c; +} +nav[data-toggle='toc'] .nav > .active > a, +nav[data-toggle='toc'] .nav > .active:hover > a, +nav[data-toggle='toc'] .nav > .active:focus > a { + padding-left: 18px; + font-weight: bold; + color: #563d7c; + background-color: transparent; + border-left: 2px solid #563d7c; +} + +/* Nav: second level (shown on .active) */ +nav[data-toggle='toc'] .nav .nav { + display: none; /* Hide by default, but at >768px, show it */ + padding-bottom: 10px; +} +nav[data-toggle='toc'] .nav .nav > li > a { + padding-top: 1px; + padding-bottom: 1px; + padding-left: 30px; + font-size: 12px; + font-weight: normal; +} +nav[data-toggle='toc'] .nav .nav > li > a:hover, +nav[data-toggle='toc'] .nav .nav > li > a:focus { + padding-left: 29px; +} +nav[data-toggle='toc'] .nav .nav > .active > a, +nav[data-toggle='toc'] .nav .nav > .active:hover > a, +nav[data-toggle='toc'] .nav .nav > .active:focus > a { + padding-left: 28px; + font-weight: 500; +} + +/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */ +nav[data-toggle='toc'] .nav > .active > ul { + display: block; +} diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js new file mode 100644 index 0000000..1cdd573 --- /dev/null +++ b/docs/bootstrap-toc.js @@ -0,0 +1,159 @@ +/*! + * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/) + * Copyright 2015 Aidan Feldman + * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */ +(function() { + 'use strict'; + + window.Toc = { + helpers: { + // return all matching elements in the set, or their descendants + findOrFilter: function($el, selector) { + // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/ + // http://stackoverflow.com/a/12731439/358804 + var $descendants = $el.find(selector); + return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])'); + }, + + generateUniqueIdBase: function(el) { + var text = $(el).text(); + var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-'); + return anchor || el.tagName.toLowerCase(); + }, + + generateUniqueId: function(el) { + var anchorBase = this.generateUniqueIdBase(el); + for (var i = 0; ; i++) { + var anchor = anchorBase; + if (i > 0) { + // add suffix + anchor += '-' + i; + } + // check if ID already exists + if (!document.getElementById(anchor)) { + return anchor; + } + } + }, + + generateAnchor: function(el) { + if (el.id) { + return el.id; + } else { + var anchor = this.generateUniqueId(el); + el.id = anchor; + return anchor; + } + }, + + createNavList: function() { + return $('
    '); + }, + + createChildNavList: function($parent) { + var $childList = this.createNavList(); + $parent.append($childList); + return $childList; + }, + + generateNavEl: function(anchor, text) { + var $a = $(''); + $a.attr('href', '#' + anchor); + $a.text(text); + var $li = $('
  • '); + $li.append($a); + return $li; + }, + + generateNavItem: function(headingEl) { + var anchor = this.generateAnchor(headingEl); + var $heading = $(headingEl); + var text = $heading.data('toc-text') || $heading.text(); + return this.generateNavEl(anchor, text); + }, + + // Find the first heading level (`

    `, then `

    `, etc.) that has more than one element. Defaults to 1 (for `

    `). + getTopLevel: function($scope) { + for (var i = 1; i <= 6; i++) { + var $headings = this.findOrFilter($scope, 'h' + i); + if ($headings.length > 1) { + return i; + } + } + + return 1; + }, + + // returns the elements for the top level, and the next below it + getHeadings: function($scope, topLevel) { + var topSelector = 'h' + topLevel; + + var secondaryLevel = topLevel + 1; + var secondarySelector = 'h' + secondaryLevel; + + return this.findOrFilter($scope, topSelector + ',' + secondarySelector); + }, + + getNavLevel: function(el) { + return parseInt(el.tagName.charAt(1), 10); + }, + + populateNav: function($topContext, topLevel, $headings) { + var $context = $topContext; + var $prevNav; + + var helpers = this; + $headings.each(function(i, el) { + var $newNav = helpers.generateNavItem(el); + var navLevel = helpers.getNavLevel(el); + + // determine the proper $context + if (navLevel === topLevel) { + // use top level + $context = $topContext; + } else if ($prevNav && $context === $topContext) { + // create a new level of the tree and switch to it + $context = helpers.createChildNavList($prevNav); + } // else use the current $context + + $context.append($newNav); + + $prevNav = $newNav; + }); + }, + + parseOps: function(arg) { + var opts; + if (arg.jquery) { + opts = { + $nav: arg + }; + } else { + opts = arg; + } + opts.$scope = opts.$scope || $(document.body); + return opts; + } + }, + + // accepts a jQuery object, or an options object + init: function(opts) { + opts = this.helpers.parseOps(opts); + + // ensure that the data attribute is in place for styling + opts.$nav.attr('data-toggle', 'toc'); + + var $topContext = this.helpers.createChildNavList(opts.$nav); + var topLevel = this.helpers.getTopLevel(opts.$scope); + var $headings = this.helpers.getHeadings(opts.$scope, topLevel); + this.helpers.populateNav($topContext, topLevel, $headings); + } + }; + + $(function() { + $('nav[data-toggle="toc"]').each(function(i, el) { + var $nav = $(el); + Toc.init($nav); + }); + }); +})(); diff --git a/docs/docsearch.css b/docs/docsearch.css new file mode 100644 index 0000000..e5f1fe1 --- /dev/null +++ b/docs/docsearch.css @@ -0,0 +1,148 @@ +/* Docsearch -------------------------------------------------------------- */ +/* + Source: https://github.com/algolia/docsearch/ + License: MIT +*/ + +.algolia-autocomplete { + display: block; + -webkit-box-flex: 1; + -ms-flex: 1; + flex: 1 +} + +.algolia-autocomplete .ds-dropdown-menu { + width: 100%; + min-width: none; + max-width: none; + padding: .75rem 0; + background-color: #fff; + background-clip: padding-box; + border: 1px solid rgba(0, 0, 0, .1); + box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175); +} + +@media (min-width:768px) { + .algolia-autocomplete .ds-dropdown-menu { + width: 175% + } +} + +.algolia-autocomplete .ds-dropdown-menu::before { + display: none +} + +.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] { + padding: 0; + background-color: rgb(255,255,255); + border: 0; + max-height: 80vh; +} + +.algolia-autocomplete .ds-dropdown-menu .ds-suggestions { + margin-top: 0 +} + +.algolia-autocomplete .algolia-docsearch-suggestion { + padding: 0; + overflow: visible +} + +.algolia-autocomplete .algolia-docsearch-suggestion--category-header { + padding: .125rem 1rem; + margin-top: 0; + font-size: 1.3em; + font-weight: 500; + color: #00008B; + border-bottom: 0 +} + +.algolia-autocomplete .algolia-docsearch-suggestion--wrapper { + float: none; + padding-top: 0 +} + +.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column { + float: none; + width: auto; + padding: 0; + text-align: left +} + +.algolia-autocomplete .algolia-docsearch-suggestion--content { + float: none; + width: auto; + padding: 0 +} + +.algolia-autocomplete .algolia-docsearch-suggestion--content::before { + display: none +} + +.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header { + padding-top: .75rem; + margin-top: .75rem; + border-top: 1px solid rgba(0, 0, 0, .1) +} + +.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column { + display: block; + padding: .1rem 1rem; + margin-bottom: 0.1; + font-size: 1.0em; + font-weight: 400 + /* display: none */ +} + +.algolia-autocomplete .algolia-docsearch-suggestion--title { + display: block; + padding: .25rem 1rem; + margin-bottom: 0; + font-size: 0.9em; + font-weight: 400 +} + +.algolia-autocomplete .algolia-docsearch-suggestion--text { + padding: 0 1rem .5rem; + margin-top: -.25rem; + font-size: 0.8em; + font-weight: 400; + line-height: 1.25 +} + +.algolia-autocomplete .algolia-docsearch-footer { + width: 110px; + height: 20px; + z-index: 3; + margin-top: 10.66667px; + float: right; + font-size: 0; + line-height: 0; +} + +.algolia-autocomplete .algolia-docsearch-footer--logo { + background-image: url("data:image/svg+xml;utf8,"); + background-repeat: no-repeat; + background-position: 50%; + background-size: 100%; + overflow: hidden; + text-indent: -9000px; + width: 100%; + height: 100%; + display: block; + transform: translate(-8px); +} + +.algolia-autocomplete .algolia-docsearch-suggestion--highlight { + color: #FF8C00; + background: rgba(232, 189, 54, 0.1) +} + + +.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight { + box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5) +} + +.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content { + background-color: rgba(192, 192, 192, .15) +} diff --git a/docs/docsearch.js b/docs/docsearch.js new file mode 100644 index 0000000..b35504c --- /dev/null +++ b/docs/docsearch.js @@ -0,0 +1,85 @@ +$(function() { + + // register a handler to move the focus to the search bar + // upon pressing shift + "/" (i.e. "?") + $(document).on('keydown', function(e) { + if (e.shiftKey && e.keyCode == 191) { + e.preventDefault(); + $("#search-input").focus(); + } + }); + + $(document).ready(function() { + // do keyword highlighting + /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */ + var mark = function() { + + var referrer = document.URL ; + var paramKey = "q" ; + + if (referrer.indexOf("?") !== -1) { + var qs = referrer.substr(referrer.indexOf('?') + 1); + var qs_noanchor = qs.split('#')[0]; + var qsa = qs_noanchor.split('&'); + var keyword = ""; + + for (var i = 0; i < qsa.length; i++) { + var currentParam = qsa[i].split('='); + + if (currentParam.length !== 2) { + continue; + } + + if (currentParam[0] == paramKey) { + keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20")); + } + } + + if (keyword !== "") { + $(".contents").unmark({ + done: function() { + $(".contents").mark(keyword); + } + }); + } + } + }; + + mark(); + }); +}); + +/* Search term highlighting ------------------------------*/ + +function matchedWords(hit) { + var words = []; + + var hierarchy = hit._highlightResult.hierarchy; + // loop to fetch from lvl0, lvl1, etc. + for (var idx in hierarchy) { + words = words.concat(hierarchy[idx].matchedWords); + } + + var content = hit._highlightResult.content; + if (content) { + words = words.concat(content.matchedWords); + } + + // return unique words + var words_uniq = [...new Set(words)]; + return words_uniq; +} + +function updateHitURL(hit) { + + var words = matchedWords(hit); + var url = ""; + + if (hit.anchor) { + url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor; + } else { + url = hit.url + '?q=' + escape(words.join(" ")); + } + + return url; +} diff --git a/docs/index.html b/docs/index.html new file mode 100644 index 0000000..9aa80e4 --- /dev/null +++ b/docs/index.html @@ -0,0 +1,149 @@ + + + + + + + +Pharmacometric and Pharmacokinetic Toolkit • pmxTools + + + + + + + + + + +
    +
    + + + + +
    +
    +
    +

    +pmxTools

    +

    Pharmacometric Tools for Modeling & Simulation

    +

    Build Status contributions welcome

    + +

    Developed by Justin Wilkins, Bill Denney and Rik Schoemaker, with contributions from a host of others.

    +

    Pharmacometric tools for common data analytical tasks; closed-form solutions for calculating concentrations at given times after dosing based on compartmental PK models (1-compartment, 2-compartment and 3-compartment, covering infusions, zero- and first-order absorption, and lag times, after single doses and at steady state, per Bertrand & Mentre (2008) http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf); parametric simulation from NONMEM-generated parameter estimates and other output; and parsing, tabulating and plotting results generated by Perl-speaks-NONMEM (PsN).

    +

    To install:

    +
    devtools::install_github("kestrel99/pmxTools")
    +

    or download directly from CRAN.

    +
    +
    + + +
    + + +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + diff --git a/docs/link.svg b/docs/link.svg new file mode 100644 index 0000000..88ad827 --- /dev/null +++ b/docs/link.svg @@ -0,0 +1,12 @@ + + + + + + diff --git a/docs/news/index.html b/docs/news/index.html new file mode 100644 index 0000000..9258c6b --- /dev/null +++ b/docs/news/index.html @@ -0,0 +1,181 @@ + + + + + + + + +Changelog • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Changelog

    + Source: NEWS.md +
    + +
    +

    +pmxTools 1.21 Unreleased +

    + +
    +
    +

    +pmxTools 1.20 Unreleased +

    +
      +

    • Rewrote plot_scm function to produce tree diagrams via DiagrammeR.

      • +

    • Fixed a rare bug in get_auc in which measurements from different individuals could be erroneously mixed.

      • +

    • Amended (or added) read_nm(), read_nm_all(), read_nmext(), read_nmcov(), read_nmtables() functions to allow reading of multiple NONMEM estimation steps.

      • +

    • Clarified documentation for calc_derived().

      • +

    • Now using xml2 to read NONMEM-generated XML files.

      • +

    • Fixed partial argument match warnings encountered during tests.

      • +

    • Add function for calculting geometric CV.

      • +
    +
    +
    + + + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/pkgdown.css b/docs/pkgdown.css new file mode 100644 index 0000000..c01e592 --- /dev/null +++ b/docs/pkgdown.css @@ -0,0 +1,367 @@ +/* Sticky footer */ + +/** + * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/ + * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css + * + * .Site -> body > .container + * .Site-content -> body > .container .row + * .footer -> footer + * + * Key idea seems to be to ensure that .container and __all its parents__ + * have height set to 100% + * + */ + +html, body { + height: 100%; +} + +body { + position: relative; +} + +body > .container { + display: flex; + height: 100%; + flex-direction: column; +} + +body > .container .row { + flex: 1 0 auto; +} + +footer { + margin-top: 45px; + padding: 35px 0 36px; + border-top: 1px solid #e5e5e5; + color: #666; + display: flex; + flex-shrink: 0; +} +footer p { + margin-bottom: 0; +} +footer div { + flex: 1; +} +footer .pkgdown { + text-align: right; +} +footer p { + margin-bottom: 0; +} + +img.icon { + float: right; +} + +img { + max-width: 100%; +} + +/* Fix bug in bootstrap (only seen in firefox) */ +summary { + display: list-item; +} + +/* Typographic tweaking ---------------------------------*/ + +.contents .page-header { + margin-top: calc(-60px + 1em); +} + +dd { + margin-left: 3em; +} + +/* Section anchors ---------------------------------*/ + +a.anchor { + margin-left: -30px; + display:inline-block; + width: 30px; + height: 30px; + visibility: hidden; + + background-image: url(./link.svg); + background-repeat: no-repeat; + background-size: 20px 20px; + background-position: center center; +} + +.hasAnchor:hover a.anchor { + visibility: visible; +} + +@media (max-width: 767px) { + .hasAnchor:hover a.anchor { + visibility: hidden; + } +} + + +/* Fixes for fixed navbar --------------------------*/ + +.contents h1, .contents h2, .contents h3, .contents h4 { + padding-top: 60px; + margin-top: -40px; +} + +/* Navbar submenu --------------------------*/ + +.dropdown-submenu { + position: relative; +} + +.dropdown-submenu>.dropdown-menu { + top: 0; + left: 100%; + margin-top: -6px; + margin-left: -1px; + border-radius: 0 6px 6px 6px; +} + +.dropdown-submenu:hover>.dropdown-menu { + display: block; +} + +.dropdown-submenu>a:after { + display: block; + content: " "; + float: right; + width: 0; + height: 0; + border-color: transparent; + border-style: solid; + border-width: 5px 0 5px 5px; + border-left-color: #cccccc; + margin-top: 5px; + margin-right: -10px; +} + +.dropdown-submenu:hover>a:after { + border-left-color: #ffffff; +} + +.dropdown-submenu.pull-left { + float: none; +} + +.dropdown-submenu.pull-left>.dropdown-menu { + left: -100%; + margin-left: 10px; + border-radius: 6px 0 6px 6px; +} + +/* Sidebar --------------------------*/ + +#pkgdown-sidebar { + margin-top: 30px; + position: -webkit-sticky; + position: sticky; + top: 70px; +} + +#pkgdown-sidebar h2 { + font-size: 1.5em; + margin-top: 1em; +} + +#pkgdown-sidebar h2:first-child { + margin-top: 0; +} + +#pkgdown-sidebar .list-unstyled li { + margin-bottom: 0.5em; +} + +/* bootstrap-toc tweaks ------------------------------------------------------*/ + +/* All levels of nav */ + +nav[data-toggle='toc'] .nav > li > a { + padding: 4px 20px 4px 6px; + font-size: 1.5rem; + font-weight: 400; + color: inherit; +} + +nav[data-toggle='toc'] .nav > li > a:hover, +nav[data-toggle='toc'] .nav > li > a:focus { + padding-left: 5px; + color: inherit; + border-left: 1px solid #878787; +} + +nav[data-toggle='toc'] .nav > .active > a, +nav[data-toggle='toc'] .nav > .active:hover > a, +nav[data-toggle='toc'] .nav > .active:focus > a { + padding-left: 5px; + font-size: 1.5rem; + font-weight: 400; + color: inherit; + border-left: 2px solid #878787; +} + +/* Nav: second level (shown on .active) */ + +nav[data-toggle='toc'] .nav .nav { + display: none; /* Hide by default, but at >768px, show it */ + padding-bottom: 10px; +} + +nav[data-toggle='toc'] .nav .nav > li > a { + padding-left: 16px; + font-size: 1.35rem; +} + +nav[data-toggle='toc'] .nav .nav > li > a:hover, +nav[data-toggle='toc'] .nav .nav > li > a:focus { + padding-left: 15px; +} + +nav[data-toggle='toc'] .nav .nav > .active > a, +nav[data-toggle='toc'] .nav .nav > .active:hover > a, +nav[data-toggle='toc'] .nav .nav > .active:focus > a { + padding-left: 15px; + font-weight: 500; + font-size: 1.35rem; +} + +/* orcid ------------------------------------------------------------------- */ + +.orcid { + font-size: 16px; + color: #A6CE39; + /* margins are required by official ORCID trademark and display guidelines */ + margin-left:4px; + margin-right:4px; + vertical-align: middle; +} + +/* Reference index & topics ----------------------------------------------- */ + +.ref-index th {font-weight: normal;} + +.ref-index td {vertical-align: top;} +.ref-index .icon {width: 40px;} +.ref-index .alias {width: 40%;} +.ref-index-icons .alias {width: calc(40% - 40px);} +.ref-index .title {width: 60%;} + +.ref-arguments th {text-align: right; padding-right: 10px;} +.ref-arguments th, .ref-arguments td {vertical-align: top;} +.ref-arguments .name {width: 20%;} +.ref-arguments .desc {width: 80%;} + +/* Nice scrolling for wide elements --------------------------------------- */ + +table { + display: block; + overflow: auto; +} + +/* Syntax highlighting ---------------------------------------------------- */ + +pre { + word-wrap: normal; + word-break: normal; + border: 1px solid #eee; +} + +pre, code { + background-color: #f8f8f8; + color: #333; +} + +pre code { + overflow: auto; + word-wrap: normal; + white-space: pre; +} + +pre .img { + margin: 5px 0; +} + +pre .img img { + background-color: #fff; + display: block; + height: auto; +} + +code a, pre a { + color: #375f84; +} + +a.sourceLine:hover { + text-decoration: none; +} + +.fl {color: #1514b5;} +.fu {color: #000000;} /* function */ +.ch,.st {color: #036a07;} /* string */ +.kw {color: #264D66;} /* keyword */ +.co {color: #888888;} /* comment */ + +.message { color: black; font-weight: bolder;} +.error { color: orange; font-weight: bolder;} +.warning { color: #6A0366; font-weight: bolder;} + +/* Clipboard --------------------------*/ + +.hasCopyButton { + position: relative; +} + +.btn-copy-ex { + position: absolute; + right: 0; + top: 0; + visibility: hidden; +} + +.hasCopyButton:hover button.btn-copy-ex { + visibility: visible; +} + +/* headroom.js ------------------------ */ + +.headroom { + will-change: transform; + transition: transform 200ms linear; +} +.headroom--pinned { + transform: translateY(0%); +} +.headroom--unpinned { + transform: translateY(-100%); +} + +/* mark.js ----------------------------*/ + +mark { + background-color: rgba(255, 255, 51, 0.5); + border-bottom: 2px solid rgba(255, 153, 51, 0.3); + padding: 1px; +} + +/* vertical spacing after htmlwidgets */ +.html-widget { + margin-bottom: 10px; +} + +/* fontawesome ------------------------ */ + +.fab { + font-family: "Font Awesome 5 Brands" !important; +} + +/* don't display links in code chunks when printing */ +/* source: https://stackoverflow.com/a/10781533 */ +@media print { + code a:link:after, code a:visited:after { + content: ""; + } +} diff --git a/docs/pkgdown.js b/docs/pkgdown.js new file mode 100644 index 0000000..7e7048f --- /dev/null +++ b/docs/pkgdown.js @@ -0,0 +1,108 @@ +/* http://gregfranko.com/blog/jquery-best-practices/ */ +(function($) { + $(function() { + + $('.navbar-fixed-top').headroom(); + + $('body').css('padding-top', $('.navbar').height() + 10); + $(window).resize(function(){ + $('body').css('padding-top', $('.navbar').height() + 10); + }); + + $('[data-toggle="tooltip"]').tooltip(); + + var cur_path = paths(location.pathname); + var links = $("#navbar ul li a"); + var max_length = -1; + var pos = -1; + for (var i = 0; i < links.length; i++) { + if (links[i].getAttribute("href") === "#") + continue; + // Ignore external links + if (links[i].host !== location.host) + continue; + + var nav_path = paths(links[i].pathname); + + var length = prefix_length(nav_path, cur_path); + if (length > max_length) { + max_length = length; + pos = i; + } + } + + // Add class to parent
  • , and enclosing
  • if in dropdown + if (pos >= 0) { + var menu_anchor = $(links[pos]); + menu_anchor.parent().addClass("active"); + menu_anchor.closest("li.dropdown").addClass("active"); + } + }); + + function paths(pathname) { + var pieces = pathname.split("/"); + pieces.shift(); // always starts with / + + var end = pieces[pieces.length - 1]; + if (end === "index.html" || end === "") + pieces.pop(); + return(pieces); + } + + // Returns -1 if not found + function prefix_length(needle, haystack) { + if (needle.length > haystack.length) + return(-1); + + // Special case for length-0 haystack, since for loop won't run + if (haystack.length === 0) { + return(needle.length === 0 ? 0 : -1); + } + + for (var i = 0; i < haystack.length; i++) { + if (needle[i] != haystack[i]) + return(i); + } + + return(haystack.length); + } + + /* Clipboard --------------------------*/ + + function changeTooltipMessage(element, msg) { + var tooltipOriginalTitle=element.getAttribute('data-original-title'); + element.setAttribute('data-original-title', msg); + $(element).tooltip('show'); + element.setAttribute('data-original-title', tooltipOriginalTitle); + } + + if(ClipboardJS.isSupported()) { + $(document).ready(function() { + var copyButton = ""; + + $(".examples, div.sourceCode").addClass("hasCopyButton"); + + // Insert copy buttons: + $(copyButton).prependTo(".hasCopyButton"); + + // Initialize tooltips: + $('.btn-copy-ex').tooltip({container: 'body'}); + + // Initialize clipboard: + var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', { + text: function(trigger) { + return trigger.parentNode.textContent; + } + }); + + clipboardBtnCopies.on('success', function(e) { + changeTooltipMessage(e.trigger, 'Copied!'); + e.clearSelection(); + }); + + clipboardBtnCopies.on('error', function() { + changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy'); + }); + }); + } +})(window.jQuery || window.$) diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml new file mode 100644 index 0000000..c442d57 --- /dev/null +++ b/docs/pkgdown.yml @@ -0,0 +1,7 @@ +pandoc: 2.7.3 +pkgdown: 1.5.1 +pkgdown_sha: ~ +articles: + pk-curves: pk-curves.html +last_built: 2020-08-25T08:03Z + diff --git a/docs/reference/calc_derived.html b/docs/reference/calc_derived.html new file mode 100644 index 0000000..6da60ae --- /dev/null +++ b/docs/reference/calc_derived.html @@ -0,0 +1,308 @@ + + + + + + + + +Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment +linear model. — calc_derived • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment +linear model.

    + Source: R/calc_derived.R + +
    + +
    +

    Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment +linear model.

    +
    + + 
    calc_derived(..., verbose = FALSE)
+
+calc_derived_1cpt(
+  CL,
+  V = NULL,
+  V1 = NULL,
+  ka = NULL,
+  tlag = NULL,
+  type = "all",
+  sigdig = 5
+)
+
+calc_derived_2cpt(
+  CL,
+  V1 = NULL,
+  V2,
+  Q2 = NULL,
+  V = NULL,
+  Q = NULL,
+  ka = NULL,
+  tlag = NULL,
+  type = "all",
+  sigdig = 5
+)
+
+calc_derived_3cpt(
+  CL,
+  V1 = NULL,
+  V2,
+  V3,
+  Q2 = NULL,
+  Q3,
+  V = NULL,
+  Q = NULL,
+  ka = NULL,
+  tlag = NULL,
+  type = "all",
+  sigdig = 5
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    ...

    Passed to the other calc_derived_*() functions.

    verbose

    For calc_derived(), provide a message indicating the +type of model detected.

    CL

    Clearance (volume per time units, e.g. L/h)

    V1, V

    Central volume of distribution (volume units, e.g. L). Values +are synonyms; use only one.

    ka

    Absorption rate (inverse time units, e.g. 1/h)

    tlag

    Absorption lag time (time units, e.g. h)

    type

    Parameters to return. Default is "all". If not +"all", this may be a vector from the names of the return value list.

    sigdig

    Number of significant digits to be returned. Default is +5.

    V2

    First peripheral volume of distribution (volume units, e.g. L)

    Q2, Q

    Intercompartmental clearance from central to first peripheral +compartment (volume per time units, e.g. L/h). Values are synonyms; use +only one.

    V3

    Second peripheral volume of distribution (volume units, e.g. L)

    Q3

    Intercompartmental clearance from central to second peripheral +compartment (volume per time units, e.g. L/h)

    + +

    Value

    + +

    Return a list of derived PK parameters for a 1-, 2-, or 3-compartment + linear model given provided clearances and volumes based on the + type.

      +

    • Vss: Volume of distribution at steady state, \(V_{ss}\) (volume units, e.g. L); 1-, 2-, and 3-compartment

      • +

    • k10: First-order elimination rate, \(k_{10}\) (inverse time units, e.g. 1/h); 1-, 2-, and 3-compartment

      • +

    • k12: First-order rate of transfer from central to first peripheral compartment, \(k_{12}\) (inverse time units, e.g. 1/h); 2- and 3-compartment

      • +

    • k21: First-order rate of transfer from first peripheral to central compartment, \(k_{21}\) (inverse time units, e.g. 1/h); 2- and 3-compartment

      • +

    • k13: First-order rate of transfer from central to second peripheral compartment, \(k_{13}\) (inverse time units, e.g. 1/h); 3-compartment

      • +

    • k31: First-order rate of transfer from second peripheral to central compartment,\(k_{31}\) (inverse time units, e.g. 1/h); 3-compartment

      • +

    • thalf_alpha: \(t_{1/2,\alpha}\) (time units, e.g. h); 1-, 2-, and 3-compartment

      • +

    • thalf_beta: \(t_{1/2,\beta}\) (time units, e.g. h); 2- and 3-compartment

      • +

    • thalf_gamma: \(t_{1/2,\gamma}\) (time units, e.g. h); 3-compartment

      • +

    • alpha: \(\alpha\); 1-, 2-, and 3-compartment

      • +

    • beta: \(\beta\); 2- and 3-compartment

      • +

    • gamma: \(\beta\); 3-compartment

      • +

    • trueA: true A; 1-, 2-, and 3-compartment

      • +

    • trueB: true B; 2- and 3-compartment

      • +

    • trueC: true C; 3-compartment

      • +

    • fracA: fractional A; 1-, 2-, and 3-compartment

      • +

    • fracB: fractional B; 2- and 3-compartment

      • +

    • fracC: fractional C; 3-compartment

      • +
    + +

    The input parameters with standardized names (V1, V2, +V3, CL, Q2, and Q3) are also returned in the +list, and if provided, additional PK parameters of `ka` and `lag` are also +returned in the list. All inputs may be scalars or vectors.

    +

    References

    + +

    Shafer S. L. CONVERT.XLS

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and + Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & + Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    params <- calc_derived(CL=29.4, V1=23.4, V2=114, V3=4614, Q2=270, Q3=73)
+params <- calc_derived_1cpt(CL=16, V=25)
+params <- calc_derived_2cpt(CL=16, V1=25, V2=50, Q=0.5)
+params <- calc_derived_3cpt(CL=29.4, V1=23.4, V2=114, V3=4614, Q2=270, Q3=73)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/calc_sd_1cmt.html b/docs/reference/calc_sd_1cmt.html new file mode 100644 index 0000000..7fd88ad --- /dev/null +++ b/docs/reference/calc_sd_1cmt.html @@ -0,0 +1,228 @@ + + + + + + + + +Calculate C(t) for a 1-compartment linear model — calc_sd_1cmt • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate C(t) for a 1-compartment linear model

    + Source: R/calc_1cmt.R + +
    + +
    +

    Calculate C(t) for a 1-compartment linear model

    +
    + + 
    calc_sd_1cmt(t, dose, dur = NULL, tinf = NULL, ...)
+
+calc_sd_1cmt_linear_bolus(t, dose, ...)
+
+calc_sd_1cmt_linear_oral_1_lag(t, dose, ...)
+
+calc_sd_1cmt_linear_infusion(t, dose, tinf, ...)
+
+calc_sd_1cmt_linear_oral_0(t, dose, dur, ...)
+
+calc_sd_1cmt_linear_oral_1(t, dose, ...)
+
+calc_sd_1cmt_linear_oral_0_lag(t, dose, dur, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    t

    Time after dose (h)

    dose

    Dose

    dur

    Duration of zero-order absorption (h)

    tinf

    Duration of infusion (h)

    ...

    Passed to `calc_derived_1cpt()`

    + +

    Value

    + +

    Concentration of drug at requested time (t) after a single dose, given provided set of parameters and variables.

    +

    Functions

    + + +
      +

    • calc_sd_1cmt_linear_bolus: Calculate C(t) for a 1-compartment linear model after a single IV bolus dose

      • +

    • calc_sd_1cmt_linear_oral_1_lag: Calculate C(t) for a 1-compartment linear model with first-order absorption after a single oral dose, with lag time

      • +

    • calc_sd_1cmt_linear_infusion: Calculate C(t) for a 1-compartment linear model after a single IV infusion

      • +

    • calc_sd_1cmt_linear_oral_0: Calculate C(t) for a 1-compartment linear model with zero-order absorption after a single oral dose

      • +

    • calc_sd_1cmt_linear_oral_1: Calculate C(t) for a 1-compartment linear model with first-order absorption after a single oral dose

      • +

    • calc_sd_1cmt_linear_oral_0_lag: Calculate C(t) for a 1-compartment linear model with zero-order absorption after a single oral dose, with lag time

      • +
    +

    References

    + +

    Bertrand J & Mentre F (2008). Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models +implemented in the Monolix software. http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    Ct <- calc_sd_1cmt_linear_bolus(t=0:24, CL=6, V=25, dose=600)
+Ct <- calc_sd_1cmt_linear_oral_1_lag(t=0:24, CL=6, V=25, ka=1.1, dose=600, tlag=2)
+Ct <- calc_sd_1cmt_linear_infusion(t=0:24, CL=6, V=25, dose=600, tinf=1)
+Ct <- calc_sd_1cmt_linear_oral_0(t=0:24, CL=6, V=25, dur=1.5, dose=600)
+Ct <- calc_sd_1cmt_linear_oral_1(t=0:24, CL=6, V=25, ka=1.1, dose=600)
+Ct <- calc_sd_1cmt_linear_oral_0_lag(t=0:24, CL=6, V=25, dur=1.5, dose=600, tlag=1.5)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/calc_sd_2cmt.html b/docs/reference/calc_sd_2cmt.html new file mode 100644 index 0000000..c421a3d --- /dev/null +++ b/docs/reference/calc_sd_2cmt.html @@ -0,0 +1,238 @@ + + + + + + + + +Calculate C(t) for a 1-compartment linear model — calc_sd_2cmt • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate C(t) for a 1-compartment linear model

    + Source: R/calc_2cmt.R + +
    + +
    +

    Calculate C(t) for a 1-compartment linear model

    +
    + + 
    calc_sd_2cmt(t, dose, dur = NULL, tinf = NULL, ...)
+
+calc_sd_2cmt_linear_bolus(t, dose, ...)
+
+calc_sd_2cmt_linear_oral_1_lag(t, dose, ...)
+
+calc_sd_2cmt_linear_infusion(t, dose, tinf, ...)
+
+calc_sd_2cmt_linear_oral_0_lag(t, dose, dur, ...)
+
+calc_sd_2cmt_linear_oral_0_lag(t, dose, dur, ...)
+
+calc_sd_2cmt_linear_oral_1(t, dose, ...)
+
+calc_sd_2cmt_linear_oral_0(t, dose, dur, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    t

    Time after dose (h)

    dose

    Dose

    dur

    Duration of zero-order absorption (h)

    tinf

    Duration of infusion (h)

    ...

    Passed to `calc_derived_2cpt()`

    + +

    Value

    + +

    Concentration of drug at requested time (t) after a single dose, given provided set of parameters and variables.

    +

    Functions

    + + +
      +

    • calc_sd_2cmt_linear_bolus: Calculate C(t) for a 2-compartment linear model after a single IV bolus dose

      • +

    • calc_sd_2cmt_linear_oral_1_lag: Calculate C(t) for a 2-compartment linear model after a single first-order oral dose with a lag time

      • +

    • calc_sd_2cmt_linear_infusion: Calculate C(t) for a 2-compartment linear model after a single infusion

      • +

    • calc_sd_2cmt_linear_oral_0_lag: Calculate C(t) for a 2-compartment linear model after a single zero-order oral dose, with lag time

      • +

    • calc_sd_2cmt_linear_oral_0_lag: Calculate C(t) for a 2-compartment linear model after a single zero-order oral dose, with lag time

      • +

    • calc_sd_2cmt_linear_oral_1: Calculate C(t) for a 2-compartment linear model after a single first-order oral dose

      • +

    • calc_sd_2cmt_linear_oral_0: Calculate C(t) for a 2-compartment linear model after a single zero-order oral dose

      • +
    +

    References

    + +

    Bertrand J & Mentre F (2008). Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models +implemented in the Monolix software. http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    Ct <- calc_sd_2cmt_linear_bolus(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5, dose = 10)
+Ct <- calc_sd_2cmt_linear_oral_1_lag(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, ka = 1, tlag = 2)
+Ctrough <- calc_sd_2cmt_linear_infusion(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 10, tinf = 1)
+Ctrough <- calc_sd_2cmt_linear_oral_0_lag(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, dur = 1, tlag=2)
+Ct <- calc_sd_2cmt_linear_oral_0_lag(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, dur = 1, tlag=2)
+Ct <- calc_sd_2cmt_linear_oral_1(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, ka = 1)
+Ct <- calc_sd_2cmt_linear_oral_0(t = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, dur = 1)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/calc_sd_3cmt.html b/docs/reference/calc_sd_3cmt.html new file mode 100644 index 0000000..bcfba25 --- /dev/null +++ b/docs/reference/calc_sd_3cmt.html @@ -0,0 +1,234 @@ + + + + + + + + +Calculate C(t) for a 1-compartment linear model — calc_sd_3cmt • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate C(t) for a 1-compartment linear model

    + Source: R/calc_3cmt.R + +
    + +
    +

    Calculate C(t) for a 1-compartment linear model

    +
    + + 
    calc_sd_3cmt(t, dose, dur = NULL, tinf = NULL, ...)
+
+calc_sd_3cmt_linear_bolus(t, dose, ...)
+
+calc_sd_3cmt_linear_oral_1_lag(t, dose, ...)
+
+calc_sd_3cmt_linear_infusion(t, dose, tinf, ...)
+
+calc_sd_3cmt_linear_oral_0(t, dose, dur, ...)
+
+calc_sd_3cmt_linear_oral_0_lag(t, dose, dur, ...)
+
+calc_sd_3cmt_linear_oral_1(t, dose, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    t

    Time after dose (h)

    dose

    Dose

    dur

    Duration of zero-order absorption (h)

    tinf

    Duration of infusion (h)

    ...

    Passed to `calc_derived_3cpt()`

    + +

    Value

    + +

    Concentration of drug at requested time (t) after a single dose, given provided set of parameters and variables.

    +

    Functions

    + + +
      +

    • calc_sd_3cmt_linear_bolus: Calculate C(t) for a 3-compartment linear model after a single IV bolus dose

      • +

    • calc_sd_3cmt_linear_oral_1_lag: Calculate C(t) for a 3-compartment linear model after a single oral dose

      • +

    • calc_sd_3cmt_linear_infusion: Calculate C(t) for a 3-compartment linear model after a single IV infusion

      • +

    • calc_sd_3cmt_linear_oral_0: Calculate C(t) for a 3-compartment linear model after a single dose, with zero-order absorption

      • +

    • calc_sd_3cmt_linear_oral_0_lag: Calculate C(t) for a 3-compartment linear model after a single dose, with zero-order absorption and a lag time

      • +

    • calc_sd_3cmt_linear_oral_1: Calculate C(t) for a 3-compartment linear model after a single oral dose

      • +
    +

    References

    + +

    Bertrand J & Mentre F (2008). Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models +implemented in the Monolix software. http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    Ct <- calc_sd_3cmt_linear_bolus(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 100)
+Ct <- calc_sd_3cmt_linear_oral_1_lag(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, ka = 1, dose = 100, tlag = 1.5)
+Ct <- calc_sd_3cmt_linear_infusion(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 100, tinf=1)
+Ct <- calc_sd_3cmt_linear_oral_0(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dur = 1, dose = 100)
+Ct <- calc_sd_3cmt_linear_oral_0_lag(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dur = 1, dose = 100, tlag=1.5)
+Ct <- calc_sd_3cmt_linear_oral_1(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, ka = 1, dose = 100)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/calc_ss_1cmt.html b/docs/reference/calc_ss_1cmt.html new file mode 100644 index 0000000..0d86bc2 --- /dev/null +++ b/docs/reference/calc_ss_1cmt.html @@ -0,0 +1,233 @@ + + + + + + + + +Calculate C(t) for a 1-compartment linear model at steady-state — calc_ss_1cmt • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate C(t) for a 1-compartment linear model at steady-state

    + Source: R/calc_1cmt.R + +
    + +
    +

    Calculate C(t) for a 1-compartment linear model at steady-state

    +
    + + 
    calc_ss_1cmt(tad, tau, dose, dur = NULL, tinf = NULL, ...)
+
+calc_ss_1cmt_linear_bolus(tad, tau, dose, ...)
+
+calc_ss_1cmt_linear_infusion(tad, tau, dose, tinf, ...)
+
+calc_ss_1cmt_linear_oral_0(tad, tau, dose, dur, ...)
+
+calc_ss_1cmt_linear_oral_0_lag(tad, tau, dose, dur, ...)
+
+calc_ss_1cmt_linear_oral_1_lag(tad, tau, dose, ...)
+
+calc_ss_1cmt_linear_oral_1(tad, tau, dose, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    tad

    Time after dose (h)

    tau

    Dosing interval (h)

    dose

    Dose

    dur

    Duration of zero-order absorption (h)

    tinf

    Duration of infusion (h)

    ...

    Passed to `calc_derived_1cpt()`

    + +

    Value

    + +

    Concentration of drug at requested time (t) after a single dose, given provided set of parameters and variables.

    +

    Functions

    + + +
      +

    • calc_ss_1cmt_linear_bolus: Calculate C(t) for a 1-compartment linear model with IV bolus dosing at steady state

      • +

    • calc_ss_1cmt_linear_infusion: Calculate C(t) for a 1-compartment linear model with infusion at steady state

      • +

    • calc_ss_1cmt_linear_oral_0: Calculate C(t) for a 1-compartment linear model with zero-order oral absorption at steady state

      • +

    • calc_ss_1cmt_linear_oral_0_lag: Calculate C(t) for a 1-compartment linear model with zero-order oral absorption at steady state, with lag time

      • +

    • calc_ss_1cmt_linear_oral_1_lag: Calculate C(t) for a 1-compartment linear model with first-order oral absorption at steady state, with lag time

      • +

    • calc_ss_1cmt_linear_oral_1: Calculate C(t) for a 1-compartment linear model with first-order oral absorption at steady state

      • +
    +

    References

    + +

    Bertrand J & Mentre F (2008). Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models +implemented in the Monolix software. http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    Ct <- calc_ss_1cmt_linear_bolus(t=0:24, CL=6, V=25, dose=600, tau=24)
+Ct <- calc_ss_1cmt_linear_infusion(tad=0:36, CL=2, V=25, dose=600, tinf=1, tau=24)
+Ct <- calc_ss_1cmt_linear_oral_0(tad=0:36, CL=2, V=25, dose=600, dur=1, tau=24)
+Ct <- calc_ss_1cmt_linear_oral_0_lag(tad=0:36, CL=2, V=25, dose=600, dur=1, tau=24, tlag=1.5)
+Ct <- calc_ss_1cmt_linear_oral_1_lag(tad=0:36, CL=2, V=25, dose=600,
+    ka=0.25, tlag=0.75, tau=24)
+Ct <- calc_ss_1cmt_linear_oral_1(tad=0:36, CL=2, V=25, dose=600, ka=0.25, tau=24)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/calc_ss_2cmt.html b/docs/reference/calc_ss_2cmt.html new file mode 100644 index 0000000..fba2a72 --- /dev/null +++ b/docs/reference/calc_ss_2cmt.html @@ -0,0 +1,238 @@ + + + + + + + + +Calculate C(t) for a 2-compartment linear model at steady-state — calc_ss_2cmt • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate C(t) for a 2-compartment linear model at steady-state

    + Source: R/calc_2cmt.R + +
    + +
    +

    Calculate C(t) for a 2-compartment linear model at steady-state

    +
    + + 
    calc_ss_2cmt(tad, tau, dose, dur = NULL, tinf = NULL, ...)
+
+calc_ss_2cmt_linear_bolus(tad, tau, dose, ...)
+
+calc_ss_2cmt_linear_infusion(tad, tau, dose, tinf, ...)
+
+calc_ss_2cmt_linear_oral_0(tad, tau, dose, dur, ...)
+
+calc_ss_2cmt_linear_oral_1_lag(tad, tau, dose, ...)
+
+calc_ss_2cmt_linear_oral_0_lag(tad, tau, dose, dur, ...)
+
+calc_ss_2cmt_linear_oral_1(tad, tau, dose, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    tad

    Time after dose (h)

    tau

    Dosing interval (h)

    dose

    Dose

    dur

    Duration of zero-order absorption (h)

    tinf

    Duration of infusion (h)

    ...

    Passed to `calc_derived_2cpt()`

    + +

    Value

    + +

    Concentration of drug at requested time (t) at steady-state, given provided set of parameters and variables.

    +

    Functions

    + + +
      +

    • calc_ss_2cmt_linear_bolus: Calculate C(t) for a 2-compartment linear model with IV bolus dosing at steady-state

      • +

    • calc_ss_2cmt_linear_infusion: Calculate C(t) for a 2-compartment linear model with infusion at steady state

      • +

    • calc_ss_2cmt_linear_oral_0: Calculate C(t) for a 2-compartment linear model at steady-state with zero-order oral dosing

      • +

    • calc_ss_2cmt_linear_oral_1_lag: Calculate C(t) for a 2-compartment linear model at steady-state with first-order oral dosing

      • +

    • calc_ss_2cmt_linear_oral_0_lag: Calculate C(t) for a 2-compartment linear model at steady-state with zero-order oral dosing and a lag time

      • +

    • calc_ss_2cmt_linear_oral_1: Calculate C(t) for a 2-compartment linear model at steady-state with first-order oral dosing

      • +
    +

    References

    + +

    Bertrand J & Mentre F (2008). Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models +implemented in the Monolix software. http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    Ct <- calc_ss_2cmt_linear_bolus(tad = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 10, tau=24)
+Ct <- calc_ss_2cmt_linear_infusion(tad = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 10, tinf = 1, tau = 12)
+Ct <- calc_ss_2cmt_linear_oral_0(tad = 23, CL = 2.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, dur = 1, tau = 24)
+Ct <- calc_ss_2cmt_linear_oral_1_lag(tad = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, ka = 1, tau=24, tlag=2)
+Ct <- calc_ss_2cmt_linear_oral_0_lag(tad = 23, CL = 2.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, dur = 1, tau = 24, tlag=2)
+Ct <- calc_ss_2cmt_linear_oral_1(tad = 11.75, CL = 7.5, V1 = 20, V2 = 30, Q = 0.5,
+    dose = 1000, ka = 1, tau=24)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/calc_ss_3cmt.html b/docs/reference/calc_ss_3cmt.html new file mode 100644 index 0000000..6930476 --- /dev/null +++ b/docs/reference/calc_ss_3cmt.html @@ -0,0 +1,238 @@ + + + + + + + + +Calculate C(t) for a 3-compartment linear model at steady-state — calc_ss_3cmt • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate C(t) for a 3-compartment linear model at steady-state

    + Source: R/calc_3cmt.R + +
    + +
    +

    Calculate C(t) for a 3-compartment linear model at steady-state

    +
    + + 
    calc_ss_3cmt(tad, tau, dose, dur = NULL, tinf = NULL, ...)
+
+calc_ss_3cmt_linear_bolus(tad, tau, dose, ...)
+
+calc_ss_3cmt_linear_oral_1_lag(tad, tau, dose, ...)
+
+calc_ss_3cmt_linear_infusion(tad, tau, dose, tinf, ...)
+
+calc_ss_3cmt_linear_oral_0(tad, tau, dose, dur, ...)
+
+calc_ss_3cmt_linear_oral_0_lag(tad, tau, dose, dur, ...)
+
+calc_ss_3cmt_linear_oral_1(tad, tau, dose, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    tad

    Time after dose (h)

    tau

    Dosing interval (h)

    dose

    Dose

    dur

    Duration of zero-order absorption (h)

    tinf

    Duration of infusion (h)

    ...

    Passed to `calc_derived_3cpt()`

    + +

    Value

    + +

    Concentration of drug at requested time (t) at steady-state, given provided set of parameters and variables.

    +

    Functions

    + + +
      +

    • calc_ss_3cmt_linear_bolus: Calculate C(t) for a 3-compartment linear model at steady state with IV bolus dosing

      • +

    • calc_ss_3cmt_linear_oral_1_lag: Calculate C(t) for a 3-compartment linear model at steady-state with first-order oral dosing with a lag time

      • +

    • calc_ss_3cmt_linear_infusion: Calculate C(t) for a 3-compartment linear model at steady state with IV infusions

      • +

    • calc_ss_3cmt_linear_oral_0: Calculate C(t) for a 3-compartment linear model at steady state, with zero-order absorption

      • +

    • calc_ss_3cmt_linear_oral_0_lag: Calculate C(t) for a 3-compartment linear model at steady state, with zero-order absorption and lag time

      • +

    • calc_ss_3cmt_linear_oral_1: Calculate C(t) for a 3-compartment linear model at steady-state with first-order oral dosing

      • +
    +

    References

    + +

    Bertrand J & Mentre F (2008). Mathematical Expressions of the Pharmacokinetic and Pharmacodynamic Models +implemented in the Monolix software. http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf

    +

    Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Lippincott Williams & Wilkins, Philadelphia, 2010.

    + +

    Examples

    + 
    Ct <- calc_ss_3cmt_linear_bolus(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dose = 100, tau=24)
+Ctrough <- calc_ss_3cmt_linear_oral_1_lag(t = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, ka = 1, dose = 100, tau=24, tlag = 1.5)
+Ct <- calc_ss_3cmt_linear_infusion(tad = 11.75, CL = 2.5, V1 = 20, V2 = 50,
+    V3 = 100, Q2 = 0.5, Q3 = 0.05, dose = 1000, tinf=1, tau=24)
+Ct <- calc_ss_3cmt_linear_oral_0(tad = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dur = 1, dose = 100, tau = 24)
+Ct <- calc_ss_3cmt_linear_oral_0_lag(tad = 11.75, CL = 3.5, V1 = 20, V2 = 500,
+    V3 = 200, Q2 = 0.5, Q3 = 0.05, dur = 1, dose = 100, tau = 24, tlag = 1.5)
+Ct <- calc_ss_3cmt_linear_oral_1(tad = 11.75, CL = 3.5, V1 = 20,
+    V2 = 500, V3 = 200, Q2 = 0.5, Q3 = 0.05, ka = 1, dose = 100, tau = 24)
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/gcv_convert.html b/docs/reference/gcv_convert.html new file mode 100644 index 0000000..c625d08 --- /dev/null +++ b/docs/reference/gcv_convert.html @@ -0,0 +1,188 @@ + + + + + + + + +Convert geometric variance or standard deviation to a geometric coefficient of variation — gcv_convert • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Convert geometric variance or standard deviation to a geometric coefficient of variation

    + Source: R/statistics.R + +
    + +
    +

    The equation used is: 100*sqrt(exp(gvar)-1)

    +
    + + 
    gcv_convert(gvar = gsd^2, gsd)
    + +

    Arguments

    + + + + + + + + + + +
    gvar

    The geometric variance (note that this is the variance not a +vector of values to compute the gcv from)

    gsd

    The geometric standard deviation

    + +

    Value

    + +

    Geometric coefficient of variation

    +

    References

    + +

    https://www.cognigen.com/nonmem/nm/99feb042003.html

    +

    http://onbiostatistics.blogspot.com/2008/07/geometric-statistics-geometric-cv-vs.html

    + +

    Examples

    + 
    gcv_convert(0.2)
    #> [1] 47.05345
    gcv_convert(gsd=0.2)
    #> [1] 20.20168
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_auc.html b/docs/reference/get_auc.html new file mode 100644 index 0000000..ec10803 --- /dev/null +++ b/docs/reference/get_auc.html @@ -0,0 +1,197 @@ + + + + + + + + +Calculate the area under the curve (AUC) for each subject over the time interval for dependent variables (<code>dv</code>) using the trapezoidal rule. — get_auc • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate the area under the curve (AUC) for each subject over the time interval for dependent variables (dv) using the trapezoidal rule.

    + Source: R/get_auc.R + +
    + +
    +

    Calculate the area under the curve (AUC) for each subject over the time interval for dependent variables (dv) using the trapezoidal rule.

    +
    + + 
    get_auc(data, time = "TIME", id = "ID", dv = "DV")
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + +
    data

    A data frame.

    time

    A string containing the name of the chronologically ordered time variable in data.

    id

    A string containing the name of the ID column (defining subject level data) in data.

    dv

    A string containing the name of the dependent variable column in data.

    + +

    Value

    + +

    A data frame containing one AUC value for every subject as defined by id.

    +

    Based on the AUC function originally written by Leonid Gibiansky in package MIfuns 5.1, from Metrum Institute.

    +

    References

    + +

    https://code.google.com/archive/p/mifuns/

    + +

    Examples

    + 
    if (FALSE) {
+ AUCs <- get_auc(myAUCdata)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_est_table.html b/docs/reference/get_est_table.html new file mode 100644 index 0000000..52dd879 --- /dev/null +++ b/docs/reference/get_est_table.html @@ -0,0 +1,207 @@ + + + + + + + + +Create a table of model parameter estimates from a NONMEM output object. — get_est_table • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Create a table of model parameter estimates from a NONMEM output object.

    + Source: R/get_est_table.R + +
    + +
    +

    Create a table of model parameter estimates from a NONMEM output object.

    +
    + + 
    get_est_table(
+  x,
+  thetaLabels = c(),
+  omegaLabels = c(),
+  sigmaLabels = c(),
+  sigdig = 3
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    x

    A NONMEM output object generated using read_nm.

    thetaLabels

    A vector containing labels for THETA parameters.

    omegaLabels

    A vector containing labels for OMEGA parameters.

    sigmaLabels

    A vector containing labels for SIGMA parameters.

    sigdig

    The desired number of significant digits to display.

    + +

    Value

    + +

    A named vector of NONMEM model parameter estimates.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmOutput <- read_nm("run315.xml")
+ estTab   <- get_est_table(nmOutput)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_omega.html b/docs/reference/get_omega.html new file mode 100644 index 0000000..0eb6a99 --- /dev/null +++ b/docs/reference/get_omega.html @@ -0,0 +1,203 @@ + + + + + + + + +Extract variability parameter estimates from a NONMEM output object. — get_omega • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Extract variability parameter estimates from a NONMEM output object.

    + Source: R/get_omega.R + +
    + +
    +

    Extract variability parameter estimates from a NONMEM output object.

    +
    + + 
    get_omega(x, output = "est", sigdig = 6, sep = "-", est.step = NULL)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    x

    A NONMEM output object generated using read_nm.

    output

    A flag specifying the matrix or matrices to be output. Valid flag values are est (the default), +se, rse, cor, cse, 95ci, or all.

    sigdig

    Specifies the number of significant digits to be provided (default=6).

    sep

    Specifies the separator character to use for 95% confidence intervals (default="-").

    est.step

    Specifies which estimation step to return parameters from (default is the last).

    + +

    Value

    + +

    A symmetrical matrix, or a list of symmetrical matrices if all is specified.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmOutput  <- read_nm("run315.xml")
+ omegas    <- get_omega(nmOutput)
+ omegaRSEs <- get_omega(nmOutput, "rse")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_probinfo.html b/docs/reference/get_probinfo.html new file mode 100644 index 0000000..c17aaa5 --- /dev/null +++ b/docs/reference/get_probinfo.html @@ -0,0 +1,190 @@ + + + + + + + + +Extract problem and estimation information from a NONMEM output object. — get_probinfo • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Extract problem and estimation information from a NONMEM output object.

    + Source: R/get_probinfo.r + +
    + +
    +

    Extract problem and estimation information from a NONMEM output object.

    +
    + + 
    get_probinfo(x, sigdig = 6, est.step = NULL)
    + +

    Arguments

    + + + + + + + + + + + + + + +
    x

    A NONMEM output object generated using read_nm.

    sigdig

    Specifies the number of significant digits to be provided (default=6).

    est.step

    Specifies which estimation step to return parameters from (default is the last).

    + +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmOutput <- read_nm("run315.xml")
+ probInfo <- get_probinfo(nmOutput)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_shrinkage.html b/docs/reference/get_shrinkage.html new file mode 100644 index 0000000..a8dcfcd --- /dev/null +++ b/docs/reference/get_shrinkage.html @@ -0,0 +1,207 @@ + + + + + + + + +Extract shrinkage estimates from a NONMEM output object. — get_shrinkage • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Extract shrinkage estimates from a NONMEM output object.

    + Source: R/get_shrinkage.R + +
    + +
    +

    Extract shrinkage estimates from a NONMEM output object.

    +
    + + 
    get_shrinkage(x, output = "eta", type = "sd", sigdig = 3, est.step = NULL)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    x

    A NONMEM output object generated using read_nm.

    output

    A flag specifying the shrinkage estimates to be output. Valid flag +values are eta (the default), epsilon, or all.

    type

    Specifies the type of shrinkage to report. Valid values are sd +(standard deviation, the default) or vr (variance, if present in the XML output).

    sigdig

    Specifies the number of significant digits to be provided (default=3).

    est.step

    Specifies which estimation step to return parameters from (default is the last).

    + +

    Value

    + +

    A named vector of NONMEM shrinkage estimates, or in the case of all, +a list of named vectors.

    +

    eta returns a vector of ETA shrinkages, as reported by NONMEM. +epsilon returns EPSILON shrinkage, as reported by NONMEM. +all returns both ETA and EPSILON shrinkage estimates as a list of vectors.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmOutput <- read_nm("run315.xml")
+ shr <- get_shrinkage(nmOutput, output="all")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_sigma.html b/docs/reference/get_sigma.html new file mode 100644 index 0000000..57664e4 --- /dev/null +++ b/docs/reference/get_sigma.html @@ -0,0 +1,211 @@ + + + + + + + + +Extract residual variability parameter estimates from a NONMEM output object. — get_sigma • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Extract residual variability parameter estimates from a NONMEM output object.

    + Source: R/get_sigma.R + +
    + +
    +

    Extract residual variability parameter estimates from a NONMEM output object.

    +
    + + 
    get_sigma(x, output = "est", sigdig = 6, sep = "-", est.step = NULL)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    x

    A NONMEM output object generated using read_nm.

    output

    A flag specifying the matrix or matrices to be output. Valid flag values are est (the default), +se, rse, cor, cse, 95ci, or all.

    sigdig

    Specifies the number of significant digits to be provided (default=6).

    sep

    Specifies the separator character to use for 95% confidence intervals (default="-").

    est.step

    Specifies which estimation step to return parameters from (default is the last).

    + +

    Value

    + +

    A symmetrical matrix, or a list of symmetrical matrices if all is specified.

    +

    est returns the estimated SIGMA variance-covariance matrix. +se returns the standard errors for the estimated SIGMA variance-covariance matrix. +rse returns the relative standard errors for the estimated SIGMA variance-covariance matrix (se/est*100). +cor returns the correlation matrix matrix. +cse returns the standard errors for the correlation matrix. +95ci returns the asymptotic 95% confidence intervals for the elements of the SIGMA variance-covariance +matrix (est +/- 1.96*se). +all returns all available SIGMA matrices.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmOutput <- read_nm("run315.xml")
+ sigmas   <- get_sigma(nmOutput)
+ sigmaRSEs <- get_sigma(nmOutput, "rse")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/get_theta.html b/docs/reference/get_theta.html new file mode 100644 index 0000000..67accb9 --- /dev/null +++ b/docs/reference/get_theta.html @@ -0,0 +1,213 @@ + + + + + + + + +Extract structural model parameter estimates and associated information +from a NONMEM output object. — get_theta • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Extract structural model parameter estimates and associated information +from a NONMEM output object.

    + Source: R/get_theta.R + +
    + +
    +

    Extract structural model parameter estimates and associated information +from a NONMEM output object.

    +
    + + 
    get_theta(x, output = "est", sigdig = 6, sep = "-", est.step = NULL)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    x

    A NONMEM output object generated using read_nm.

    output

    A flag specifying the matrix or matrices to be output. Valid flag values are est (the default), +se, rse, 95ci, or all.

    sigdig

    Specifies the number of significant digits to be provided (default=6).

    sep

    Specifies the separator character to use for 95% confidence intervals (default="-").

    est.step

    Specifies which estimation step to return parameters from (default is the last).

    + +

    Value

    + +

    A named vector of NONMEM model parameter estimates, or in the case of all, +a list of named vectors.

    +

    est returns a vector of THETA values. +se returns a vector of THETA standard errors. +rse returns a vector of THETA relative standard errors (se/est*100). +95ci returns a vector of the asymptotic 95% confidence intervals for the elements of THETA (est +/- 1.96*se). +all returns all available THETA information as a list of named vectors.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmOutput <- read_nm("run315.xml")
+ thetas <- get_theta(nmOutput)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/gm.html b/docs/reference/gm.html new file mode 100644 index 0000000..908e085 --- /dev/null +++ b/docs/reference/gm.html @@ -0,0 +1,180 @@ + + + + + + + + +Calculate geometric mean — gm • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate geometric mean

    + Source: R/statistics.R + +
    + +
    +

    Calculate geometric mean

    +
    + + 
    gm(x)
    + +

    Arguments

    + + + + + + +
    x

    Numeric vector.

    + +

    Value

    + +

    The geometric mean. NA is returned if there are any non-positive elements in x.

    + +

    Examples

    + 
    gm(c(0.5, 7, 8, 5))
    #> [1] 3.439791
    
+
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/index.html b/docs/reference/index.html new file mode 100644 index 0000000..52bc456 --- /dev/null +++ b/docs/reference/index.html @@ -0,0 +1,379 @@ + + + + + + + + +Function reference • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Reference

    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +

    All functions

    +

    +
    +

    calc_derived() calc_derived_1cpt() calc_derived_2cpt() calc_derived_3cpt()

    +

    Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment +linear model.

    +

    calc_sd_1cmt() calc_sd_1cmt_linear_bolus() calc_sd_1cmt_linear_oral_1_lag() calc_sd_1cmt_linear_infusion() calc_sd_1cmt_linear_oral_0() calc_sd_1cmt_linear_oral_1() calc_sd_1cmt_linear_oral_0_lag()

    +

    Calculate C(t) for a 1-compartment linear model

    +

    calc_sd_2cmt() calc_sd_2cmt_linear_bolus() calc_sd_2cmt_linear_oral_1_lag() calc_sd_2cmt_linear_infusion() calc_sd_2cmt_linear_oral_0_lag() calc_sd_2cmt_linear_oral_0_lag() calc_sd_2cmt_linear_oral_1() calc_sd_2cmt_linear_oral_0()

    +

    Calculate C(t) for a 1-compartment linear model

    +

    calc_sd_3cmt() calc_sd_3cmt_linear_bolus() calc_sd_3cmt_linear_oral_1_lag() calc_sd_3cmt_linear_infusion() calc_sd_3cmt_linear_oral_0() calc_sd_3cmt_linear_oral_0_lag() calc_sd_3cmt_linear_oral_1()

    +

    Calculate C(t) for a 1-compartment linear model

    +

    calc_ss_1cmt() calc_ss_1cmt_linear_bolus() calc_ss_1cmt_linear_infusion() calc_ss_1cmt_linear_oral_0() calc_ss_1cmt_linear_oral_0_lag() calc_ss_1cmt_linear_oral_1_lag() calc_ss_1cmt_linear_oral_1()

    +

    Calculate C(t) for a 1-compartment linear model at steady-state

    +

    calc_ss_2cmt() calc_ss_2cmt_linear_bolus() calc_ss_2cmt_linear_infusion() calc_ss_2cmt_linear_oral_0() calc_ss_2cmt_linear_oral_1_lag() calc_ss_2cmt_linear_oral_0_lag() calc_ss_2cmt_linear_oral_1()

    +

    Calculate C(t) for a 2-compartment linear model at steady-state

    +

    calc_ss_3cmt() calc_ss_3cmt_linear_bolus() calc_ss_3cmt_linear_oral_1_lag() calc_ss_3cmt_linear_infusion() calc_ss_3cmt_linear_oral_0() calc_ss_3cmt_linear_oral_0_lag() calc_ss_3cmt_linear_oral_1()

    +

    Calculate C(t) for a 3-compartment linear model at steady-state

    +

    gcv_convert()

    +

    Convert geometric variance or standard deviation to a geometric coefficient of variation

    +

    get_auc()

    +

    Calculate the area under the curve (AUC) for each subject over the time interval for dependent variables (dv) using the trapezoidal rule.

    +

    get_est_table()

    +

    Create a table of model parameter estimates from a NONMEM output object.

    +

    get_omega()

    +

    Extract variability parameter estimates from a NONMEM output object.

    +

    get_probinfo()

    +

    Extract problem and estimation information from a NONMEM output object.

    +

    get_shrinkage()

    +

    Extract shrinkage estimates from a NONMEM output object.

    +

    get_sigma()

    +

    Extract residual variability parameter estimates from a NONMEM output object.

    +

    get_theta()

    +

    Extract structural model parameter estimates and associated information +from a NONMEM output object.

    +

    gm()

    +

    Calculate geometric mean

    +

    pcv()

    +

    Calculate percentage coefficient of variation

    +

    pk_curve()

    +

    Provide concentration-time curves.

    +

    plot_nmprogress()

    +

    Plot NONMEM parameter estimation by iteration.

    +

    plot_scm()

    +

    Visualize PsN SCM output.

    +

    read_nm()

    +

    Read NONMEM 7.2+ output into a list of lists.

    +

    read_nmcov()

    +

    Read in the NONMEM variance-covariance matrix.

    +

    read_nmext()

    +

    Read NONMEM output into a list.

    +

    read_nmtables()

    +

    Reads NONMEM output tables.

    +

    read_nm_all()

    +

    Read all NONMEM files for a single NONMEM run.

    +

    read_nm_multi_table()

    +

    Read (single or) multiple NONMEM tables from a single file

    +

    read_nm_std_ext()

    +

    Read a standard NONMEM extension file

    +

    read_scm()

    +

    Read PsN SCM output into a format suitable for further use.

    +

    rnm()

    +

    Read NONMEM 7.2+ output into an R object.

    +

    sample_omega()

    +

    Sample from the multivariate normal distribution using the OMEGA variance-covariance matrix to generate new sets of simulated ETAs from NONMEM output.

    +

    sample_sigma()

    +

    Sample from the multivariate normal distribution using the SIGMA variance-covariance matrix to generate new sets of simulated EPSILONs from NONMEM output.

    +

    sample_uncert()

    +

    Sample from the multivariate normal distribution to generate new sets of parameters from NONMEM output.

    +

    table_rtf()

    +

    Read NONMEM output into a list.

    +
    + + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/pcv.html b/docs/reference/pcv.html new file mode 100644 index 0000000..332d2ea --- /dev/null +++ b/docs/reference/pcv.html @@ -0,0 +1,184 @@ + + + + + + + + +Calculate percentage coefficient of variation — pcv • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Calculate percentage coefficient of variation

    + Source: R/statistics.R + +
    + +
    +

    Calculate percentage coefficient of variation

    +
    + + 
    pcv(x, na.rm = FALSE)
    + +

    Arguments

    + + + + + + + + + + +
    x

    Numeric vector.

    na.rm

    A logical value indicating whether NA values should be stripped before the computation proceeds.

    + +

    Value

    + +

    The percentage coefficient of variation.

    + +

    Examples

    + 
    pcv(rnorm(50, 5, 7.56))
    #> [1] 189.4419
    
+
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
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z^nh?94ljcHLg?k#ero!C!N$#V)Y)%T%f?>b!86ZV)AEo( zN57w5u*k??Lvo-yl+jm|a3cyJG&DYBo!oyy6VtdYWU8JBq44{dZo@2?^0SK1t+Doq++#SY#O zkE*Oot!m!s5an)a9Xz-Dev?aiH@UpJXbzAoDC*mktgrrJm>~FFnz7{8d@9!uG=6^Q zY?1qkhM20DWiP*H3-9eAUEg%yoERMY)qyO%0ha)P|B5^6S4l+#^C~VNWb58(Kh;B zFA(r-JmBu^m;b!T2tJov?U~Hqd(@%Q-6E-TN0N6UdnTG#-)yv8(0jAW6n`k-nGizj z9Kfo=o^pLqRKZJgI`b?Li*%*dEA6j6-`vYgwHNJ~dDk-P=c3$`g2U7>uQPS!I)isw z?mEZu(lm4pu>*7rzD@VJJug=Z4t1X{>d$_4!u4f0W5GS(S&{+KbLz19>p7skJFjto zr}UR$SMOpB8UO5B=Si9DBBzm(-gfdwx723#(d*(}!xrG5SjW%!(O$AYi=uP;`TnBO zmrX9Z$RsT)S$XPs=GisR(#Yu|E>0-*AF$t+Bzm5$Bl{CFWs#XD=DI+>{?;WK>dFd^ z@O&wiEGF)*2Xcp1v;Qcqz&$~_tI3AsR+sWu{>ayMs9t3bGkC46(Y)YgodXB#?ERkQ z^g~Unu2UO5EoDqOKJFh+L``}={{s%@XNsrgKUhu1&0Q`xQLFKiqBKP=%(Vp+c<1yj zzTlOhuI5KaLmie~izOyYX3P&b_hsW>OmPBuI~K)mPwWHhj-706=ZaLXohX-&95w7E_ zIY)WVALPmE>~Tvyj(q-Lw)J0i)Bi>z|3CKq|0f&u@0-Rjb5ZBj!Oi8%N`(%uPioaXXUL0B;=z3<8M?cZBudUd-;#7_I$7U=e{UK#4nPsWaO^X&VH- zW$5p*Z^Bj^p_VKe%#m&2W+R%|QKG_GTVQJn?EgVnfBWB&XourD#%$@Ptq4_4`0Jp3 z2c?nP9lrM<=J|DRq%k*pSDA+3z-X@E54-=*zEt_a|6@|8>&2k1TI$-DQAcf@4wqQ@ H{rO)2Y=)Dw literal 0 HcmV?d00001 diff --git a/docs/reference/pk_curve.html b/docs/reference/pk_curve.html new file mode 100644 index 0000000..7cd86da --- /dev/null +++ b/docs/reference/pk_curve.html @@ -0,0 +1,213 @@ + + + + + + + + +Provide concentration-time curves. — pk_curve • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Provide concentration-time curves.

    + Source: R/pk_curve.R + +
    + +
    +

    Provide concentration-time curves.

    +
    + + 
    pk_curve(
+  t,
+  model = "1cmt_oral",
+  params = list(ka = 2.77, CL = 2.5, V = 25),
+  dose = 600,
+  ii = 24,
+  addl = 0,
+  ss = F
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    t

    Observation time in h, specified as a vector.

    model

    The model to use. Must be one of "1cmt_bolus", "1cmt_infusion", "1cmt_oral", "2cmt_bolus", "2cmt_infusion", +"2cmt_oral", "3cmt_bolus", "3cmt_infusion", "3cmt_oral". The default is "1cmt_oral".

    params

    A named list containing parameter values for the selected model type.

    dose

    Dose amount.

    ii

    Interdose interval (or tau), in hours (default 24).

    addl

    Number of additional doses (default 0).

    ss

    Assume steady state concentration (default FALSE).

    + +

    Value

    + +

    A data frame containing times (t) and concentrations (cp).

    + +

    Examples

    + 
    plot(pk_curve(t=seq(0,72,by=0.1), model="3cmt_oral", ii=12, addl=5,
+  params=list(CL=2.5, V1=25, V2=2, V3=5, Q2=0.5, Q3=0.25, ka=1)), type="l")
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/plot_nmprogress.html b/docs/reference/plot_nmprogress.html new file mode 100644 index 0000000..2329fb8 --- /dev/null +++ b/docs/reference/plot_nmprogress.html @@ -0,0 +1,211 @@ + + + + + + + + +Plot NONMEM parameter estimation by iteration. — plot_nmprogress • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Plot NONMEM parameter estimation by iteration.

    + Source: R/plot_nmprogress.R + +
    + +
    +

    plot_nmprogress returns a plot or set of plots showing the evolution of +parameter estimates by iteration.

    +
    + + 
    plot_nmprogress(
+  fileName,
+  fileExt = ".lst",
+  metric = "perc",
+  lineCol = "#902C10",
+  idlineCol = "black"
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    fileName

    A NONMEM output file prefix, without extension (e.g. 'run315').

    fileExt

    The file extension for NONMEM output, set to '.lst' by default.

    metric

    What to show in the plot. Allowed options are 'est' (the actual +estimate) or 'perc' (the percentage change in the estimated or OFV since estimation began). +Default is 'perc'.

    lineCol

    Line color. Default is '#902C10'.

    idlineCol

    Identity line color (only used if 'perc' metric is selected). Default is black.

    + +

    Value

    + +

    A set of plots.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+plot_nmprogress("run315")
+plot_nmprogress("run315", ".nmlst")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/plot_scm.html b/docs/reference/plot_scm.html new file mode 100644 index 0000000..30becf2 --- /dev/null +++ b/docs/reference/plot_scm.html @@ -0,0 +1,364 @@ + + + + + + + + +Visualize PsN SCM output. — plot_scm • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Visualize PsN SCM output.

    + Source: R/plot_scm.R + +
    + +
    +

    plot_scm returns a visualization of a Perl-speaks-NONMEM (PsN, https://uupharmacometrics.github.io/PsN/) SCM (stepwise covariate modeling) +procedure. It depends on the presence of scmlog.txt and short_scmlog.txt files in the +specified directory.

    +
    + + 
    plot_scm(
+  dir,
+  startPhase = "forward",
+  fwdSuccessCol = "#66C2A5",
+  fwdFailCol = "black",
+  bwdSuccessCol = "#FC8D62",
+  bwdFailCol = "black",
+  defCol = "black",
+  fwdSuccessFillCol = "#B3E2CD",
+  fwdFailFillCol = "white",
+  bwdSuccessFillCol = "#FDCDAC",
+  bwdFailFillCol = "white",
+  defFillCol = "white",
+  fwdSuccessFontCol = "black",
+  fwdFailFontCol = "black",
+  bwdSuccessFontCol = "black",
+  bwdFailFontCol = "black",
+  defFontCol = "black",
+  fullFwdCol = "#8DA0CB",
+  finalCol = "#E78AC3",
+  fullFwdFillCol = "#CBD5E8",
+  finalFillCol = "#F4CAE4",
+  fullFwdFontCol = "black",
+  finalFontCol = "black",
+  fullFwdWidth = "2px",
+  finalWidth = "2px",
+  defWidth = "1px",
+  nodeStyle = "filled,rounded",
+  nodeShape = "box",
+  fontname = "helvetica",
+  rankdir = "TB",
+  layout = "dot",
+  lookupDF = NULL,
+  ...
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    dir

    A PsN SCM folder (containing scmlog.txt and short_scmlog.txt).

    startPhase

    Where to start collating the output; can be "forward" (the default) or "backward".

    fwdSuccessCol

    Node outline color for a model fit matching the forward inclusion criterion.

    fwdFailCol

    Node outline color for a model fit not matching the forward inclusion criterion.

    bwdSuccessCol

    Node outline color for a model fit matching the backward elimination criterion.

    bwdFailCol

    Node outline color for a model fit not matching the backward elimination criterion.

    defCol

    Default node outline color.

    fwdSuccessFillCol

    Node fill color for a model fit matching the forward inclusion criterion.

    fwdFailFillCol

    Node fill color for a model fit not matching the forward inclusion criterion.

    bwdSuccessFillCol

    Node fill color for a model fit matching the backward elimination criterion.

    bwdFailFillCol

    Node fill color for a model fit not matching the backward elimination criterion.

    defFillCol

    Default node fill color.

    fwdSuccessFontCol

    Node font color for a model fit matching the forward inclusion criterion.

    fwdFailFontCol

    Node font color for a model fit not matching the forward inclusion criterion.

    bwdSuccessFontCol

    Node font color for a model fit matching the backward elimination criterion.

    bwdFailFontCol

    Node font color for a model fit not matching the backward elimination criterion.

    defFontCol

    Default node font color.

    fullFwdCol

    Node outline color for the full forward model (i.e. the final model before the backward elimination procedure in SCM).

    finalCol

    Node outline color for the final reduced model (i.e. the final model reached after the backward elimination procedure in SCM).

    fullFwdFillCol

    Node fill color for the full forward model (i.e. the final model before the backward elimination procedure in SCM).

    finalFillCol

    Node fill color for the final reduced model (i.e. the final model reached after the backward elimination procedure in SCM).

    fullFwdFontCol

    Node font color for the full forward model (i.e. the final model before the backward elimination procedure in SCM).

    finalFontCol

    Node font color for the final reduced model (i.e. the final model reached after the backward elimination procedure in SCM).

    fullFwdWidth

    Node outline width for the full forward model (i.e. the final model before the backward elimination procedure in SCM).

    finalWidth

    Node outline width for the final reduced model (i.e. the final model reached after the backward elimination procedure in SCM).

    defWidth

    Default node outline width.

    nodeStyle

    Node style. A string containing a comma-separated list of options (which include "filled", "striped", "wedged", "diagonals" and "rounded"). See the GraphViz documentation for further details.

    nodeShape

    Node shape. Options include "box" (the default), "oval", "diamond", "egg", "plaintext", "point", "square", "triangle" and many more. See the GraphViz documentation for further details.

    fontname

    Font for nodes. Options depend heavily on the local system - see the GraphViz documentation for further details.

    rankdir

    Direction of graph layout. Possible values are "TB" (the default), "LR", "BT", "RL", corresponding to directed graphs drawn from top to bottom, from left to right, from bottom to top, and from right to left, respectively.

    layout

    Graph layout. Possible values are "dot" (the default), "neato", "twopi", and "circo". Note that of these, "dot" is the easiest to interpret and the others may produce odd results.

    lookupDF

    A data frame containing a lookup table for node labels. By default, plot_scm will use the PSN model names. If a lookup table containing the fields `Model` and `Alias` is provided, model names in `Model` will be replaced in the output plots by mtaching labels in `Alias`.

    ...

    Additional parameters passed to the underlying SetNodeStyle and SetEdgeStyle functions, which in turn rely on DiagrammeR.

    + +

    Value

    + +

    A grViz object.

    +

    Details

    + +

    This function parses PsN SCM output and displays it as a GraphViz graph (effectively, an HTML widget). It is built on plot.Node - please refer to doucmentation for this function for a more detailed overview of what is possible (a lot). For more specific details, see http://rich-iannone.github.io/DiagrammeR/docs.html.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    +

    GraphViz (https://graphviz.org/Documentation.php)

    +

    Lindbom L, Ribbing J & Jonsson EN (2004). Perl-speaks-NONMEM (PsN) - A Perl module for NONMEM related programming. Computer Methods and Programs in Biomedicine, 75(2), 85-94. https://doi.org/10.1016/j.cmpb.2003.11.003

    +

    Lindbom L, Pihlgren P & Jonsson N (2005). PsN-Toolkit - A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Computer Methods and Programs in Biomedicine, 79(3), 241-257. https://doi.org/10.1016/j.cmpb.2005.04.005

    +

    Other NONMEM reading: +read_nm_all(), +read_nm_multi_table(), +read_nmcov(), +read_nmext(), +read_nmtables(), +read_nm(), +read_scm()

    + +

    Examples

    + 
    if (FALSE) {
+scm <- plot_scm("E:/DrugX/ModelDevelopment/scm310")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nm.html b/docs/reference/read_nm.html new file mode 100644 index 0000000..cf53648 --- /dev/null +++ b/docs/reference/read_nm.html @@ -0,0 +1,205 @@ + + + + + + + + +Read NONMEM 7.2+ output into a list of lists. — read_nm • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read NONMEM 7.2+ output into a list of lists.

    + Source: R/read_nm.R + +
    + +
    +

    Read NONMEM 7.2+ output into a list of lists.

    +
    + + 
    read_nm(fileName, directory = NULL, quiet = FALSE, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + +
    fileName

    A NONMEM XML output file (e.g. "run315.xml").

    directory

    The directory to look for files within. If NULL, uses the +current directory.

    quiet

    Flag for displaying intermediate output.

    ...

    Passed to each of the read functions (ignored in the functions).

    + +

    Value

    + +

    A list of lists corresponding to a NONMEM output object.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    +

    Other NONMEM reading: +plot_scm(), +read_nm_all(), +read_nm_multi_table(), +read_nmcov(), +read_nmext(), +read_nmtables(), +read_scm()

    + +

    Examples

    + 
    if (FALSE) {
+nmOutput <- read_nm("run315.xml")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nm_all.html b/docs/reference/read_nm_all.html new file mode 100644 index 0000000..e8191ef --- /dev/null +++ b/docs/reference/read_nm_all.html @@ -0,0 +1,206 @@ + + + + + + + + +Read all NONMEM files for a single NONMEM run. — read_nm_all • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read all NONMEM files for a single NONMEM run.

    + Source: R/read_nm_all.R + +
    + +
    +

    Read all NONMEM files for a single NONMEM run.

    +
    + + 
    read_nm_all(runNo, run_prefix = "run", directory = NULL, quiet = FALSE, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + +
    runNo

    Run number.

    run_prefix

    The start to the name of the run.

    directory

    The directory to look for files within. If NULL, uses the +current directory.

    quiet

    Flag for displaying intermediate output.

    ...

    Passed to each of the read functions (ignored in the functions).

    + +

    Details

    + +

    The filename for loading is constructed as paste(run_prefix, + runNo). To load a nonstandard file, simply set one of those values to + NULL.

    +

    See also

    + +

    Other NONMEM reading: +plot_scm(), +read_nm_multi_table(), +read_nmcov(), +read_nmext(), +read_nmtables(), +read_nm(), +read_scm()

    + +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nm_multi_table.html b/docs/reference/read_nm_multi_table.html new file mode 100644 index 0000000..1217669 --- /dev/null +++ b/docs/reference/read_nm_multi_table.html @@ -0,0 +1,211 @@ + + + + + + + + +Read (single or) multiple NONMEM tables from a single file — read_nm_multi_table • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read (single or) multiple NONMEM tables from a single file

    + Source: R/read_nmtables.R + +
    + +
    +

    Read (single or) multiple NONMEM tables from a single file

    +
    + + 
    read_nm_multi_table(
+  fileName,
+  header = TRUE,
+  ...,
+  simplify = TRUE,
+  table_start_pattern = "^TABLE NO"
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + +
    fileName

    The filename to read from

    header, ...

    Arguments passed to read.table

    simplify

    If a single table is present, return a data.frame instead of +a list of data.frames?

    table_start_pattern

    What should be found to start a new table?

    + +

    Value

    + +

    A list of data.frames, or if only one is present and simplify=TRUE, a + data.frame.

    +

    See also

    + +

    Other NONMEM reading: +plot_scm(), +read_nm_all(), +read_nmcov(), +read_nmext(), +read_nmtables(), +read_nm(), +read_scm()

    + +

    Examples

    + 
    if (FALSE) {
+read_nm_multi_table("run1.cov", row.names=1)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nm_std_ext.html b/docs/reference/read_nm_std_ext.html new file mode 100644 index 0000000..8282fe2 --- /dev/null +++ b/docs/reference/read_nm_std_ext.html @@ -0,0 +1,197 @@ + + + + + + + + +Read a standard NONMEM extension file — read_nm_std_ext • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read a standard NONMEM extension file

    + Source: R/read_nmtables.R + +
    + +
    +

    Read a standard NONMEM extension file

    +
    + + 
    read_nm_std_ext(fileName, extension, directory = NULL, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + +
    fileName

    The filename (with directory name, if applicable) to read +(with or without the extension)

    extension

    The file extension to optionally append (preferably starting +with a ".")

    directory

    The directory to look for files within. If NULL, uses the +current directory.

    ...

    Passed to read_nm_multi_table()

    + +

    Value

    + +

    NULL if the file does not exist or the value of + read_nm_multi_table() if it does exist.

    + +

    Examples

    + 
    if (FALSE) {
+read_nm_std_ext("run1", "phi")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nmcov.html b/docs/reference/read_nmcov.html new file mode 100644 index 0000000..a1e0106 --- /dev/null +++ b/docs/reference/read_nmcov.html @@ -0,0 +1,207 @@ + + + + + + + + +Read in the NONMEM variance-covariance matrix. — read_nmcov • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read in the NONMEM variance-covariance matrix.

    + Source: R/read_nmcov.R + +
    + +
    +

    Read in the NONMEM variance-covariance matrix.

    +
    + + 
    read_nmcov(fileName, quiet = FALSE, directory = NULL, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + +
    fileName

    Root filename for the NONMEM run (e.g. "run315").

    +

    This function reads the ".cov" NONMEM output table, and will return an error if this +is missing.

    quiet

    Flag for displaying intermediate output.

    directory

    The directory to look for files within. If NULL, uses the +current directory.

    ...

    Passed to each of the read functions (ignored in the functions).

    + +

    Value

    + +

    A symmetrical variance-covariance matrix covering all model parameters.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    +

    Other NONMEM reading: +plot_scm(), +read_nm_all(), +read_nm_multi_table(), +read_nmext(), +read_nmtables(), +read_nm(), +read_scm()

    + +

    Examples

    + 
    if (FALSE) {
+nmVcov <- read_nmcov("run315")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nmext.html b/docs/reference/read_nmext.html new file mode 100644 index 0000000..7be3927 --- /dev/null +++ b/docs/reference/read_nmext.html @@ -0,0 +1,236 @@ + + + + + + + + +Read NONMEM output into a list. — read_nmext • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read NONMEM output into a list.

    + Source: R/read_nmext.R + +
    + +
    +

    read_nmext returns a summary of a given NONMEM run, including +termination messages, parameter estimates, and precision estimates. +Minimally, the NONMEM output and '.ext' files must be available.

    +
    + + 
    read_nmext(
+  fileName,
+  fileExt = ".lst",
+  directory = NULL,
+  quiet = FALSE,
+  estNo = NULL,
+  ...
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    fileName

    A NONMEM output file prefix, without extension (e.g. +"run315").

    fileExt

    The file extension for NONMEM output, set to ".lst" by +default.

    directory

    The directory to look for files within. If NULL, uses the +current directory.

    quiet

    Flag for displaying intermediate output.

    estNo

    The estimation number to report (by default, if only one +estimation step is present, that will be reported; if multiple are +reported, the last will be reported by default).

    ...

    Passed to each of the read functions (ignored in the functions).

    + +

    Value

    + +

    A list of lists, containing 'Termination' (summary of NONMEM's + termination output, including shrinkages and ETABAR estimates), 'OFV' (the + objective function value), 'Thetas' (a vector of structural parameter + estimates, or THETAs), 'Omega', a list of lists containing the OMEGA + matrix, 'Sigma', a list of lists containing the SIGMA matrix, 'seThetas', a + vector of standard errors for THETAs, 'seOmega', a list of lists containing + standard errors for the OMEGA matrix, and 'seSigma', a list of lists + containing standard errors for the SIGMA matrix.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    +

    Other NONMEM reading: +plot_scm(), +read_nm_all(), +read_nm_multi_table(), +read_nmcov(), +read_nmtables(), +read_nm(), +read_scm()

    + +

    Examples

    + 
    if (FALSE) {
+read_nmext("run315")
+read_nmext("run315", ".nmlst")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_nmtables.html b/docs/reference/read_nmtables.html new file mode 100644 index 0000000..3560c76 --- /dev/null +++ b/docs/reference/read_nmtables.html @@ -0,0 +1,242 @@ + + + + + + + + +Reads NONMEM output tables. — read_nmtables • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Reads NONMEM output tables.

    + Source: R/read_nmtables.R + +
    + +
    +

    Reads NONMEM output tables.

    +
    + + 
    read_nmtables(
+  tableFiles = NULL,
+  runNo = NULL,
+  tabSuffix = "",
+  tableNames = c("sdtab", "mutab", "patab", "catab", "cotab", "mytab", "extra",
+    "xptab"),
+  quiet = FALSE,
+  directory = NULL,
+  output_type = c("data.frame", "list"),
+  ...
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    tableFiles

    NONMEM table files to be read.

    runNo

    Run number.

    tabSuffix

    Table file suffix.

    tableNames

    List of root table names, using the Xpose naming convention +as the default.

    quiet

    Flag for displaying intermediate output.

    directory

    The directory to look for files within. If NULL, uses the +current directory.

    output_type

    Should output be a "data.frame" where all results are +merged or a "list" of data.frames.

    ...

    Passed to each of the read functions (ignored in the functions).

    + +

    Value

    + +

    A data.frame or list of data.frames depending on the + output_type argument.

    +

    Note

    + +

    Adapted from Xpose 4 (https://CRAN.R-project.org/package=xpose4).

    +

    References

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    +

    Jonsson EN, Karlsson MO. Xpose--an S-PLUS based population + pharmacokinetic/pharmacodynamic model building aid for NONMEM. Comput + Methods Programs Biomed. 1999 Jan;58(1):51-64

    +

    See also

    + +

    Other NONMEM reading: +plot_scm(), +read_nm_all(), +read_nm_multi_table(), +read_nmcov(), +read_nmext(), +read_nm(), +read_scm()

    + +

    Examples

    + 
    if (FALSE) {
+tables <- read_nmtables(runNo=315)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/read_scm.html b/docs/reference/read_scm.html new file mode 100644 index 0000000..640e057 --- /dev/null +++ b/docs/reference/read_scm.html @@ -0,0 +1,212 @@ + + + + + + + + +Read PsN SCM output into a format suitable for further use. — read_scm • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read PsN SCM output into a format suitable for further use.

    + Source: R/read_scm.R + +
    + +
    +

    read_scm returns a summary of a Perl-speaks-NONMEM (PsN, https://uupharmacometrics.github.io/PsN/) SCM (stepwise covariate modeling) +procedure. It depends on the presence of scmlog.txt and short_scmlog.txt files in the +specified directory.

    +
    + + 
    read_scm(dir, startPhase = "forward")
    + +

    Arguments

    + + + + + + + + + + +
    dir

    A PsN SCM folder (containing scmlog.txt and short_scmlog.txt).

    startPhase

    Where to start collating the output; can be "forward" (the default) or "backward".

    + +

    Value

    + +

    A list of data frames, containing

    +
    forward

    all models evaluated during the forward inclusion step of + covariate model building

    +
    forwardSummary

    the covariate relationships selected at each forward + step

    +
    forwardP

    the P-value used for inclusion during the forward inclusion step

    +
    backward

    all models evaluated during the backward elimination step of covariate + model building

    +
    backwardSummary

    the covariate relationships eliminated at each backward step

    +
    backwardP

    the P-value used for exclusion during the backward elimination step

    + +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    +

    Lindbom L, Ribbing J & Jonsson EN (2004). Perl-speaks-NONMEM (PsN) - A Perl module for NONMEM related programming. Computer Methods and Programs in Biomedicine, 75(2), 85-94. https://doi.org/10.1016/j.cmpb.2003.11.003

    +

    Lindbom L, Pihlgren P & Jonsson N (2005). PsN-Toolkit - A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Computer Methods and Programs in Biomedicine, 79(3), 241-257. https://doi.org/10.1016/j.cmpb.2005.04.005

    +

    Other NONMEM reading: +plot_scm(), +read_nm_all(), +read_nm_multi_table(), +read_nmcov(), +read_nmext(), +read_nmtables(), +read_nm()

    + +

    Examples

    + 
    if (FALSE) {
+scm <- read_scm("E:/DrugX/ModelDevelopment/scm310")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/rnm.html b/docs/reference/rnm.html new file mode 100644 index 0000000..847579f --- /dev/null +++ b/docs/reference/rnm.html @@ -0,0 +1,262 @@ + + + + + + + + +Read NONMEM 7.2+ output into an R object. — rnm • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read NONMEM 7.2+ output into an R object.

    + Source: R/rnm.R + +
    + +
    +

    Read NONMEM 7.2+ output into an R object.

    +
    + + 
    rnm(
+  index,
+  prefix = "run",
+  pathNM,
+  ndig = 3,
+  ndigB = 3,
+  ndigP = 1,
+  Pci = 95,
+  ext = ".lst",
+  extmod = ".mod",
+  Pvalues = TRUE,
+  RawCI = FALSE,
+  ...
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    index

    The NONMEM model index, i.e. the numeric part of the filename assuming it follows the convention 'run123.mod'.

    prefix

    The NONMEM model prefix, assuming it follows the convention 'run123.mod'. The default is "run".

    pathNM

    The path to the NONMEM output. This should not contain a trailing slash.

    ndig

    Number of significant digits to use. The default is 3.

    ndigB

    Number of significant digits to use. The default is 3.

    ndigP

    Number of digits after the decimal point to use for percentages. The default is 1.

    Pci

    Asymptotic confidence interval to apply when reporting parameter uncertainty. The default is 95.

    ext

    NONMEM output file extension. The default is ".lst".

    extmod

    NONMEM control stream file extension. The default is "mod".

    Pvalues

    Report P-values for parameters? The default is TRUE.

    RawCI

    Report confidence intervals without estimate? The default is FALSE.

    ...

    Additional arguments.

    + +

    Value

    + +

    A list containing information extracted from the NONMEM output.

    +

    Details

    + +

    The output list is composed of the following objects:

      +

    • "Theta"A data frame describing the structural (fixed-effect) parameters, containing parameter name, estimated value, standard error (SE), coefficient of variation (CV), lower and upper confidence limits (CIL and CIU, based on Pci), and P-value, calculated as 2 * (1 - pnorm(abs(theta/theta.se))).

      • +

    • "Eta"A data frame describing the interindividual random-effects parameters, containing estimated value, standard error (SE), coefficient of variation (CV, calculated as abs(100*(SE/OMEGA))), coefficient of variation (EtaCV, calculated as 100*sqrt(OMEGA)), and shrinkage.

      • +

    • "Epsilon"A data frame describing the residual random-effects parameters, containing estimated value, standard error (SE), coefficient of variation (CV, calculated as abs(100*(SE/OMEGA))), coefficient of variation (EtaCV, calculated as 100*sqrt(SIGMA)), and shrinkage.

      • +

    • "CorTheta"A data frame containing the correlation matrix for fixed effects ("THETA").

      • +

    • "CorOmega"A data frame containing the correlation matrix for interindividual random effects ("OMEGA").

      • +

    • "CorSigma"A data frame containing the correlation matrix for residual random effects ("OMEGA").

      • +

    • "OmegaMatrix"A data frame containing the "OMEGA" matrix.

      • +

    • "SigmaMatrix"A data frame containing the "OMEGA" matrix.

      • +

    • "CovMatrixTheta"A data frame containing the variance-covariance matrix for structural parameters (THETA).

      • +

    • "CovMatrix"A data frame containing the complete variance-covariance matrix.

      • +

    • "OFV"The objective function value.

      • +

    • "ThetaString"A data frame containing all relevant fixed-effects parameter information, suitable for use in a table of parameter estimates. Contains parameter name, estimate, standard error, coefficient of variation, combined estimate and asymptotic confidence interval, and P-value.

      • +

    • "EtaString"A data frame containing all relevant interindivudal random-effects parameter information, suitable for use in a table of parameter estimates. Contains parameter name, estimate (variance), standard error, coefficient of variation, percentage value (calculated as 100*sqrt(OMEGA)), and shrinkage.

      • +

    • "EpsString"A data frame containing all relevant residual random-effects parameter information, suitable for use in a table of parameter estimates. Contains parameter name, estimate (variance), standard error, coefficient of variation, percentage value (calculated as 100*sqrt(SIGMA)), and shrinkage.

      • +

    • "RunTime"Run time.

      • +

    • "ConditionN"Condition number.

      • +
    + +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+nmOutput <- rnm("run315.lst")
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/sample_omega.html b/docs/reference/sample_omega.html new file mode 100644 index 0000000..ebfa9fb --- /dev/null +++ b/docs/reference/sample_omega.html @@ -0,0 +1,194 @@ + + + + + + + + +Sample from the multivariate normal distribution using the OMEGA variance-covariance matrix to generate new sets of simulated ETAs from NONMEM output. — sample_omega • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Sample from the multivariate normal distribution using the OMEGA variance-covariance matrix to generate new sets of simulated ETAs from NONMEM output.

    + Source: R/sample_omega.R + +
    + +
    +

    Sample from the multivariate normal distribution using the OMEGA variance-covariance matrix to generate new sets of simulated ETAs from NONMEM output.

    +
    + + 
    sample_omega(nmRun, n, seed)
    + +

    Arguments

    + + + + + + + + + + + + + + +
    nmRun

    Root filename for the NONMEM run (e.g. "run315").

    n

    Number of samples required.

    seed

    Random seed.

    + +

    Value

    + +

    A data frame containing n samples from the multivariate normal distribution, using +the estimated NONMEM OMEGA variance-covariance matrix. This provides n sets of ETA estimates +suitable for simulation of new patients.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ omDist <- sample_omega("run315", 5000, seed=740727)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/sample_sigma.html b/docs/reference/sample_sigma.html new file mode 100644 index 0000000..79d29e8 --- /dev/null +++ b/docs/reference/sample_sigma.html @@ -0,0 +1,194 @@ + + + + + + + + +Sample from the multivariate normal distribution using the SIGMA variance-covariance matrix to generate new sets of simulated EPSILONs from NONMEM output. — sample_sigma • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Sample from the multivariate normal distribution using the SIGMA variance-covariance matrix to generate new sets of simulated EPSILONs from NONMEM output.

    + Source: R/sample_sigma.R + +
    + +
    +

    Sample from the multivariate normal distribution using the SIGMA variance-covariance matrix to generate new sets of simulated EPSILONs from NONMEM output.

    +
    + + 
    sample_sigma(nmRun, n, seed)
    + +

    Arguments

    + + + + + + + + + + + + + + +
    nmRun

    Root filename for the NONMEM run (e.g. "run315").

    n

    Number of samples required.

    seed

    Random seed.

    + +

    Value

    + +

    A data frame containing n samples from the multivariate normal distribution, using +the estimated NONMEM SIGMA variance-covariance matrix. This provides n sets of EPSILON estimates +suitable for simulation of new datasets.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ sigDist <- sample_sigma("run315", 5000, seed=740727)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/sample_uncert.html b/docs/reference/sample_uncert.html new file mode 100644 index 0000000..23b039d --- /dev/null +++ b/docs/reference/sample_uncert.html @@ -0,0 +1,195 @@ + + + + + + + + +Sample from the multivariate normal distribution to generate new sets of parameters from NONMEM output. — sample_uncert • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Sample from the multivariate normal distribution to generate new sets of parameters from NONMEM output.

    + Source: R/sample_uncert.R + +
    + +
    +

    Sample from the multivariate normal distribution to generate new sets of parameters from NONMEM output.

    +
    + + 
    sample_uncert(nmRun, n, seed)
    + +

    Arguments

    + + + + + + + + + + + + + + +
    nmRun

    Root filename for the NONMEM run (e.g. "run315").

    n

    Number of samples required.

    seed

    Random seed.

    + +

    Value

    + +

    A data frame containing n samples from the multivariate normal distribution, using +NONMEM typical parameter estimates the NONMEM variance-covariance matrix (from the *.cov file). This +provides n sets of parameter estimates sampled from the uncertainty distribution, suitable +for simulation under model uncertainty.

    +

    See also

    + +

    NONMEM (http://www.iconplc.com/innovation/nonmem/)

    + +

    Examples

    + 
    if (FALSE) {
+ nmMatrix <- sample_uncert("run315", 5000, seed=740727)
+}
    +
    + +
    + + +
    +
    +

    Developed by Justin Wilkins, Bill Denney, Rik Schoemaker.

    +
    + +
    +

    Site built with pkgdown 1.5.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/reference/table_rtf.html b/docs/reference/table_rtf.html new file mode 100644 index 0000000..1a91e47 --- /dev/null +++ b/docs/reference/table_rtf.html @@ -0,0 +1,212 @@ + + + + + + + + +Read NONMEM output into a list. — table_rtf • pmxTools + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    Read NONMEM output into a list.

    + Source: R/table_rtf.R + +
    + +
    +

    table_rtf generates an RTF table from a data frame.

    +
    + + 
    table_rtf(
+  df,
+  outFile = NULL,
+  rtfFile = TRUE,
+  boldHeader = TRUE,
+  rowNames = FALSE,
+  ...
+)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    df

    A data frame.

    outFile

    A filename for writing the table to. If NULL, writes to console.

    rtfFile

    If TRUE (the default), then add RTF tabs to generate a fully formatted RTF file.

    boldHeader

    If TRUE, make the header bold.

    rowNames

    If TRUE, include row names in the table. Default is FALSE.

    ...

    Other formatting options for the table body.

    + +

    Value

    + +

    An RTF table based on the data frame provided.

    +

    References

    + +

    https://www.r-bloggers.com/another-solution-to-the-r-to-word-table-problem/

    + +

    Examples

    + 
    if (FALSE) {
+scm <- read_scm("E:/DrugX/ModelDevelopment/scm310")
+myRTF <- table_rtf(scm$forwardSummary)
+}
    +
    + +
    + + + +
    + + + + + + + +